WO2023173929A1 - 编解码方法和装置 - Google Patents

编解码方法和装置 Download PDF

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Publication number
WO2023173929A1
WO2023173929A1 PCT/CN2023/072525 CN2023072525W WO2023173929A1 WO 2023173929 A1 WO2023173929 A1 WO 2023173929A1 CN 2023072525 W CN2023072525 W CN 2023072525W WO 2023173929 A1 WO2023173929 A1 WO 2023173929A1
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probe data
normalization
target
normalized
combination
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PCT/CN2023/072525
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English (en)
French (fr)
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林泽辉
蔡康颖
陈虎
魏榕
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华为技术有限公司
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    • G—PHYSICS
    • G06—COMPUTING; CALCULATING OR COUNTING
    • G06F—ELECTRIC DIGITAL DATA PROCESSING
    • G06F3/00—Input arrangements for transferring data to be processed into a form capable of being handled by the computer; Output arrangements for transferring data from processing unit to output unit, e.g. interface arrangements
    • G06F3/06—Digital input from, or digital output to, record carriers, e.g. RAID, emulated record carriers or networked record carriers
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING OR COUNTING
    • G06F—ELECTRIC DIGITAL DATA PROCESSING
    • G06F3/00—Input arrangements for transferring data to be processed into a form capable of being handled by the computer; Output arrangements for transferring data from processing unit to output unit, e.g. interface arrangements
    • G06F3/06—Digital input from, or digital output to, record carriers, e.g. RAID, emulated record carriers or networked record carriers
    • G06F3/0601—Interfaces specially adapted for storage systems
    • G06F3/0602—Interfaces specially adapted for storage systems specifically adapted to achieve a particular effect
    • G06F3/0608—Saving storage space on storage systems
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING OR COUNTING
    • G06F—ELECTRIC DIGITAL DATA PROCESSING
    • G06F3/00—Input arrangements for transferring data to be processed into a form capable of being handled by the computer; Output arrangements for transferring data from processing unit to output unit, e.g. interface arrangements
    • G06F3/06—Digital input from, or digital output to, record carriers, e.g. RAID, emulated record carriers or networked record carriers
    • G06F3/0601—Interfaces specially adapted for storage systems
    • G06F3/0628—Interfaces specially adapted for storage systems making use of a particular technique
    • G06F3/0638—Organizing or formatting or addressing of data
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING OR COUNTING
    • G06T—IMAGE DATA PROCESSING OR GENERATION, IN GENERAL
    • G06T15/00—3D [Three Dimensional] image rendering
    • G06T15/50—Lighting effects
    • G06T15/55—Radiosity
    • H—ELECTRICITY
    • H04—ELECTRIC COMMUNICATION TECHNIQUE
    • H04N—PICTORIAL COMMUNICATION, e.g. TELEVISION
    • H04N19/00—Methods or arrangements for coding, decoding, compressing or decompressing digital video signals
    • H04N19/10—Methods or arrangements for coding, decoding, compressing or decompressing digital video signals using adaptive coding
    • H04N19/169—Methods or arrangements for coding, decoding, compressing or decompressing digital video signals using adaptive coding characterised by the coding unit, i.e. the structural portion or semantic portion of the video signal being the object or the subject of the adaptive coding
    • H04N19/17—Methods or arrangements for coding, decoding, compressing or decompressing digital video signals using adaptive coding characterised by the coding unit, i.e. the structural portion or semantic portion of the video signal being the object or the subject of the adaptive coding the unit being an image region, e.g. an object
    • H04N19/172—Methods or arrangements for coding, decoding, compressing or decompressing digital video signals using adaptive coding characterised by the coding unit, i.e. the structural portion or semantic portion of the video signal being the object or the subject of the adaptive coding the unit being an image region, e.g. an object the region being a picture, frame or field
    • H—ELECTRICITY
    • H04—ELECTRIC COMMUNICATION TECHNIQUE
    • H04N—PICTORIAL COMMUNICATION, e.g. TELEVISION
    • H04N19/00—Methods or arrangements for coding, decoding, compressing or decompressing digital video signals
    • H04N19/50—Methods or arrangements for coding, decoding, compressing or decompressing digital video signals using predictive coding
    • H04N19/597—Methods or arrangements for coding, decoding, compressing or decompressing digital video signals using predictive coding specially adapted for multi-view video sequence encoding
    • H—ELECTRICITY
    • H04—ELECTRIC COMMUNICATION TECHNIQUE
    • H04N—PICTORIAL COMMUNICATION, e.g. TELEVISION
    • H04N19/00—Methods or arrangements for coding, decoding, compressing or decompressing digital video signals
    • H04N19/70—Methods or arrangements for coding, decoding, compressing or decompressing digital video signals characterised by syntax aspects related to video coding, e.g. related to compression standards

Definitions

  • the embodiments of the present application relate to the field of media technology, and in particular, to encoding and decoding methods and devices.
  • Probes are one of the common means of simulating lighting effects in rendering systems.
  • the number of probes in a single scenario often reaches thousands or even hundreds of thousands for large-scale scenarios. Since probe data can change over time, storing, accessing, and transmitting probe data generates a large amount of overhead. To this end, it is necessary to compress probe data to reduce the cost of storage, access and transmission of probe data.
  • Embodiments of the present application provide encoding and decoding methods and devices, which can reduce rendering losses caused by compressing probe data.
  • the embodiments of this application adopt the following technical solutions:
  • embodiments of the present application provide a coding method, which method includes: first determining a target normalized combination of a probe data set, and then normalizing the probe data set according to the target normalized combination. Normalize to obtain a normalized probe data set, and then encode the normalized probe data set into a code stream.
  • the target normalization combination is a normalization combination that minimizes the rendering loss corresponding to the probe data group among multiple normalization combinations, and the target normalization combination includes a target normalization method and a target Normalization parameters.
  • the probe data corresponds to one or more probes in the three-dimensional scene and is used to determine the coloring effect of the objects in the three-dimensional scene during the rendering process.
  • the probe data set may include probe data for a single row of probes in one or more frames, probe data for a single probe in one or more frames, probe data for a single channel probe in one or more frames. data or probe data for all probes in one or more frames.
  • the encoding method provided by the embodiment of the present application does not use a certain fixed normalization method and normalization parameters during the normalization process, but selects from multiple normalization methods and normalization parameters. Among the combinations, select the combination of normalization method and normalization parameters that minimizes the rendering loss corresponding to the probe data. Compared with using fixed normalization methods and normalization parameters, normalization using a combination of normalization methods and normalization parameters that minimizes the rendering loss corresponding to probe data can reduce the effects of compressing probe data. rendering loss.
  • the rendering loss corresponding to the probe data group can be probe data The error between the rendering effect corresponding to the group and the rendering effect corresponding to the encoded and decoded probe data group.
  • the above rendering loss can be measured by the peak signal to noise ratio (PSNR), the root mean squared error (MSE) or other parameters. This is not the case in the embodiments of this application. limited.
  • determining the target normalization combination of the probe data group may include: determining the corresponding normalization combination of each of the multiple normalization combinations for the probe data group. rendering loss; determine the normalization combination that minimizes the rendering loss corresponding to the probe data group among the multiple normalization combinations as the target normalization combination.
  • the normalization combination is determined as the target normalization combination, and then the normalization method is used to minimize the rendering loss corresponding to the probe data and the combination of normalization parameters (i.e., the target normalization combination) is used for normalization, which can reduce Rendering loss caused by compressing (normalizing) probe data.
  • the above determination of the rendering loss corresponding to the probe data group for each of the multiple normalization combinations may include: according to each of the normalization combinations Perform a target operation on the probe data group to obtain the rendering result of each normalized combination for the probe data group; the rendering result obtained by rendering through the target operation according to the probe data group and The rendering result obtained by rendering the probe data group without the target operation determines the rendering loss corresponding to each normalized combination for the probe data group.
  • the target operations include normalization, encoding and decoding, and denormalization.
  • the specific encoding and decoding methods mentioned above can be processed by any method that can be thought of by those skilled in the art, and the embodiments of the present application do not specifically limit this.
  • the specific encoding and decoding methods can be high efficiency video coding (HEVC), analog encoding and decoding, low resolution encoding and decoding, fast encoding and decoding and other encoding and decoding methods.
  • HEVC high efficiency video coding
  • analog encoding and decoding analog encoding and decoding
  • low resolution encoding and decoding low resolution encoding and decoding
  • fast encoding and decoding and other encoding and decoding methods other encoding and decoding methods.
  • the rendering result corresponding to each normalized combination can be obtained, and then by comparing the rendering results obtained by the target operation on the probe data group and The rendering result obtained by the probe data without target operation can obtain the rendering loss corresponding to each normalized combination for the probe data group. Then use the normalization combination that minimizes the rendering loss corresponding to the probe data for normalization, which can reduce the rendering loss caused by compressing (normalizing) the probe data.
  • the above method may further include: encoding the target normalized combination into the code stream.
  • the decoder can quickly obtain the target normalized combination of the probe data group by decoding the code stream, and then use the target normalized The combination performs denormalization on the normalized probe data set to obtain the probe data set.
  • the above-mentioned encoding of the target normalized combination into the code stream may include: when the probe data set is a probe data set through intra-frame coding, The target normalized combination is encoded into the code stream.
  • Intra-frame coding is a coding method that only uses the current frame information when encoding the current frame.
  • the intra-frame coding of HE VC can be used to complete the intra-frame coding of the probe data group; inter-frame coding is used when encoding the current frame.
  • the inter-frame coding of HEVC can be used to complete the inter-frame coding of the probe data group.
  • the above method may further include: determining the change amount of the normalization parameter of the probe data set according to the target normalization parameter of the probe data set and the reference target normalization parameter;
  • the normalization parameters Variations are encoded into the code stream.
  • the reference target normalization parameter is a target normalization parameter of a probe data set related to the probe data set.
  • determining whether a probe data group is related to the current probe data group can be measured through a variety of measurement methods.
  • the embodiments of the present application are not limited to this, which include but are not limited to, calculating two probe data groups. If the Pearson correlation coefficient is greater than the second preset threshold, one of the two probe data sets is considered to be related to the other; in addition, the two probe data can also be calculated PSNR between groups, if the PSNR is greater than the preset threshold, one of the two probe data groups is considered to be related to the other group.
  • encoding the normalized parameter variation of the probe data group into the code stream can reduce the overhead, and when the probe data is After the group's normalized parameter changes are encoded into the code stream, the decoder can quickly obtain the normalized parameter changes of the probe data group by decoding the code stream, and then determine the probe data group through the normalized parameter changes.
  • the target normalization combination is then used to denormalize the normalized probe data set through the target normalization combination to obtain the probe data set.
  • the above-mentioned encoding of the normalized parameter variation into the code stream may include: when the probe data set is a probe data set through inter-frame coding, The normalized parameter variation is encoded into the code stream.
  • the above method may further include: determining the normalization parameter change amount of the probe data set according to the target normalization parameter of the probe data set and the reference target normalization parameter,
  • the reference target normalization parameter is the target normalization parameter of the probe data group related to the probe data group; first information is encoded into the code stream, and the first information is used to indicate the Whether the target normalization parameter of the probe data set changes compared with the reference target normalization parameter.
  • the reference target normalization parameter of the probe data group of the current frame may be the target normalization parameter of the probe data group of the previous frame of the current frame.
  • the first information may use different flag bits to indicate whether the target normalization parameter of the probe data set changes compared with the reference target normalization parameter.
  • the above method may further include: when the first information indicates that the target normalization parameter of the probe data group changes compared with the reference target normalization parameter, The normalized parameter variation is encoded into the code stream.
  • the target normalization parameter of the probe data set changes compared with the reference target normalization parameter, compared with encoding the target normalization combination of the probe data set into the code stream
  • Encoding the normalized parameter changes of the probe data group into the code stream can reduce overhead, and after encoding the normalized parameter changes of the probe data group into the code stream, the decoder can quickly obtain it by decoding the code stream.
  • the change amount of the normalized parameters of the probe data set is then used to determine the target normalized combination of the probe data set, and then the normalized probe data set is processed through the target normalized combination. Denormalize to obtain the probe data set.
  • the above method may further include: encoding index information into the code stream, where the index information includes the identification of the probe data group and the normalized parameter variation of the probe data group. .
  • the above method may further include: determining the normalization parameters in the multiple normalization combinations according to the reference target normalization parameter, where the reference target normalization parameter is equal to The target normalization parameter of the probe data set associated with the probe data set.
  • the target normalization parameters of the probe data set can be specified in the target normalization parameters of the reference target normalization parameters. is within the range of 1/(1+ ⁇ ) times to 1+ ⁇ times. Among them, ⁇ can range from 0.01 to 0.05.
  • the above-mentioned multiple normalization combinations may be a normalization combination composed of a min-max normalization method and multiple normalization parameters.
  • the normalization parameters can include the maximum normalization parameter and the minimum normalization parameter, and the normalization formula can satisfy:
  • M is the maximum normalization parameter
  • m is the minimum normalization parameter
  • the target normalization parameters (such as M and m) of the probe data group of the current frame can be 1/(1+ ⁇ ) times to 1 of the target normalization parameters of the probe data group of the previous frame.
  • ⁇ can range from 0.01 to 0.05.
  • the target normalization parameter M of the data ranges from 0.99 to 1.01.
  • the target normalization method can also be other normalization methods.
  • the maximum value normalization method or the standard score (Z-Score) normalization method is preset.
  • the above-mentioned probe data includes the surrounding environment data of the probe, and the surrounding environment data includes illumination data, color, visibility data (including distance data, variance of distance data, square of distance data, etc.), material, At least one of normal or texture coordinates.
  • the probe data includes the probe's surrounding environment data and the probe's attribute data. Since the attribute data of a probe usually occupies much less storage space than the surrounding environment data, the method provided by the embodiments of the present application can only process the surrounding environment data of the probe.
  • embodiments of the present application also provide a decoding method, which method includes: first decoding the code stream to obtain a normalized probe data set.
  • the normalized probe data set is then denormalized according to the target normalized combination of the first probe data set to obtain a second probe data set. Rendering is then performed based on the second probe data set.
  • the target normalized combination is the normalized combination with the smallest rendering loss corresponding to the first probe data group among multiple normalized combinations
  • the first probe data group is the normalized combination before normalization.
  • the normalized probe data set, the target normalization combination includes a target normalization method and a target normalization parameter.
  • the normalized probe data can be obtained by decoding the code stream. Then use a combination of normalization method and normalization parameters that minimizes the rendering loss corresponding to the probe data to perform denormalization to obtain the probe data. Compared with using a fixed normalization method and normalization parameters to perform denormalization, Normalize the probe data obtained by using a normalized combination that minimizes the rendering loss corresponding to the probe data. The rendering loss caused by the probe data is small during rendering, thus reducing the impact caused by compressing the probe data. Rendering loss.
  • the rendering loss (rendering loss) corresponding to the probe data group can be the error between the rendering effect corresponding to the probe data group and the rendering effect corresponding to the encoded and decoded probe data group.
  • the above-mentioned rendering loss can be measured by peak signal to noise ratio (PSNR), root mean square error (mean squared error, MSE) or other parameters. This is not the case in the embodiments of this application. limited.
  • the above method may further include: obtaining the target normalized combination.
  • obtaining the target normalized combination may include: obtaining target information, The information includes the target normalized combination.
  • obtaining the target normalized combination may include: decoding the code stream to obtain the target normalized combination.
  • the decoding method provided by the embodiment of the present application can obtain the normalized probe data by decoding the code stream and a combination of the normalization method and normalization parameters that minimizes the rendering loss corresponding to the probe data. Then use this normalization combination to perform denormalization to obtain probe data. Compared with using a fixed normalization method and normalization parameters to perform denormalization, the probe data obtained is made to correspond to the probe data using The probe data is obtained by the normalized combination with the smallest rendering loss, which brings less rendering loss during rendering, thus reducing the rendering loss caused by compressing the probe data.
  • the above-mentioned acquisition of the target normalized combination may include: decoding the code stream to obtain the normalized parameter variation of the first probe data group; according to the normalized
  • the target normalization combination is determined by the change amount of the parameter and the reference normalization combination, and the reference normalization combination is the target normalization combination of the probe data set related to the first probe data set.
  • the target normalization method in the target normalization combination may be the same as the target normalization method in the reference normalization combination.
  • the decoding method provided by the embodiment of the present application can obtain the normalized probe data and the normalized parameter variation by decoding the code stream, and then obtain the normalized parameter variation by combining the normalized parameter variation with the reference normalization.
  • the combination of normalization method and normalization parameters that minimizes the rendering loss corresponding to the probe data. Then use this normalization combination to perform denormalization to obtain probe data.
  • the probe data obtained is made to correspond to the probe data using The probe data is obtained by the normalized combination with the smallest rendering loss, which brings less rendering loss during rendering, thus reducing the rendering loss caused by compressing the probe data.
  • the above-described acquisition of the target normalized combination may include: decoding the code stream to obtain first information, the first information being used to indicate the first probe data group Whether the target normalization parameter changes compared with the reference target normalization parameter, the reference target normalization parameter is the target normalization parameter of the probe data group related to the first probe data group; When the first information indicates that the target normalization parameter of the first probe data group has not changed compared with the reference target normalization parameter, the target normalization is determined according to the reference normalization combination.
  • the reference normalization combination is a target normalization combination of probe data sets related to the first probe data set; when the first information indicates the target normalization combination of the first probe data set When the normalization parameter changes from the reference target normalization parameter, decode the code stream to obtain second information, and the second information is used to indicate the normalization parameter of the first probe data group
  • the change amount is determined according to the normalization parameter change amount and the reference normalization combination.
  • the target normalization combination may be the same as the reference normalization combination.
  • the target normalization combination may be combined with the The reference normalization combination is the same.
  • the decoding method provided by the embodiment of the present application can obtain the normalized probe data and target information by decoding the code stream, and then obtain the normalization method and target information that minimize the rendering loss corresponding to the probe data through the target information.
  • a combination of normalization parameters Then use this normalization combination to perform denormalization to obtain probe data.
  • the probe data obtained is made to correspond to the probe data using The probe data is obtained by the normalized combination with the smallest rendering loss, which brings less rendering loss during rendering, thus reducing the rendering loss caused by compressing the probe data.
  • embodiments of the present application also provide an encoding device, which includes: a data form conversion module and an encoding module; the data form conversion module is used to determine the target normalized combination of the probe data group and combine it according to The target normalization combination normalizes the probe data set to obtain a normalized probe data set, and the target normalization combination is to make the probe data set among multiple normalization combinations.
  • the target normalization combination includes a target normalization method and a target normalization parameter; the encoding module is used to compile the normalized probe data group into code stream.
  • the data form conversion module is specifically configured to: determine the rendering loss corresponding to each of the multiple normalized combinations for the probe data group; convert the Among multiple normalization combinations, the normalization combination that minimizes the rendering loss corresponding to the probe data group is determined as the target normalization combination.
  • the data form conversion module is specifically configured to: perform a target operation on the probe data group according to each normalized combination to obtain the value of each normalized combination for each
  • the rendering result of the probe data set, the target operation includes normalization, encoding, decoding, and denormalization; the rendering result obtained by rendering the probe data set through the target operation and the probe data
  • a set of rendering results obtained by rendering without the target operation determines the rendering loss corresponding to each normalized combination for the probe data set.
  • the encoding module is further configured to encode the target normalized combination into the code stream.
  • the data form conversion module is further configured to: determine the normalization of the probe data set according to the target normalization parameter of the probe data set and the reference target normalization parameter.
  • Parameter change amount the reference target normalization parameter is the target normalization parameter of the probe data set related to the probe data set;
  • the encoding module is also configured to encode the normalized parameter variation into the code stream.
  • the encoding module is also configured to encode first information into the code stream, where the first information is used to indicate that the target normalization parameter of the probe data group is relatively Whether the reference target normalization parameter changes.
  • the encoding module is also configured to: when the first information indicates that the target normalization parameter of the probe data group changes compared with the reference target normalization parameter , the normalized parameter variation is encoded into the code stream.
  • the encoding module is also configured to encode index information into the code stream, where the index information includes an identification of the probe data group and a normalized parameter of the probe data group. amount of change.
  • the data form conversion module is further configured to: determine the normalization parameters in the multiple normalization combinations according to the reference target normalization parameters, the reference target normalization The parameter is the target normalization parameter of the probe data set associated with the probe data set.
  • the probe data set includes surrounding environment data of the probe, and the surrounding environment data includes at least one of lighting data, color, visibility data, material, normal or texture coordinates. .
  • embodiments of the present application also provide a decoding device, which includes: a decoding module and a data form conversion module; the decoding module is used to decode the code stream to obtain the normalized probe data set; the A data form conversion module, configured to denormalize the normalized probe data set according to the target normalized combination of the first probe data set to obtain a second probe data set and generate the second probe data set according to the target normalization combination of the first probe data set.
  • the target data group is rendered, and the target normalized combination is the normalized combination with the smallest rendering loss corresponding to the first probe data group among multiple normalized combinations.
  • the first probe number The data set is the normalized probe data set before normalization, and the target normalization combination includes a target normalization method and a target normalization parameter.
  • the decoding module is also used to obtain the target normalized combination.
  • the decoding module is specifically configured to: decode the code stream to obtain the target normalized combination.
  • the decoding module is specifically configured to: decode the code stream to obtain the normalized parameter variation of the first probe data group; and according to the normalized parameter variation and The target normalization combination is determined with a reference normalization combination, which is a target normalization combination of probe data sets related to the first probe data set.
  • the decoding module is specifically configured to decode the code stream to obtain first information, where the first information is used to indicate the target normalization parameter of the first probe data group. Whether there is a change compared to the reference target normalization parameter, which is the target normalization parameter of the probe data group related to the first probe data group; in the first information When indicating that the target normalization parameter of the first probe data group has not changed compared with the reference target normalization parameter, the target normalization combination is determined according to the reference normalization combination, and the reference normalization combination is The normalized combination is a target normalized combination of probe data sets related to the first probe data set; when the first information indicates that the target normalized parameter of the first probe data set is smaller than the When the reference target normalization parameter changes, decode the code stream to obtain the normalization parameter variation of the first probe data group and perform normalization according to the normalization parameter variation and the reference normalization ization combination determines the target normalization combination.
  • embodiments of the present application further provide a coding device, which includes: at least one processor.
  • a coding device which includes: at least one processor.
  • the at least one processor executes program codes or instructions, the first aspect or any possible implementation thereof is implemented. the method described in .
  • the device may further include at least one memory for storing the program code or instructions.
  • embodiments of the present application further provide a decoding device.
  • the device includes: at least one processor.
  • the at least one processor executes program codes or instructions, the above second aspect or any possible implementation thereof is implemented. the method described in .
  • the device may further include at least one memory for storing the program code or instructions.
  • embodiments of the present application further provide a chip, including: an input interface, an output interface, and at least one processor.
  • the chip also includes memory.
  • the at least one processor is used to execute the code in the memory.
  • the chip implements the method described in the above first aspect or any possible implementation manner thereof.
  • the above-mentioned chip may also be an integrated circuit.
  • embodiments of the present application further provide a computer-readable storage medium for storing a computer program.
  • the computer program includes a method for implementing the method described in the above-mentioned first aspect or any possible implementation manner thereof.
  • embodiments of the present application also provide a computer program product containing instructions that, when run on a computer, cause the computer to implement the method described in the above first aspect or any possible implementation thereof.
  • the encoding and decoding device, computer storage medium, computer program product and chip provided in this embodiment are all used to execute the encoding and decoding method provided above. Therefore, the beneficial effects that can be achieved can refer to the encoding and decoding method provided above. middle The beneficial effects will not be repeated here.
  • Figure 1a is an exemplary block diagram of a coding and decoding system provided by an embodiment of the present application
  • Figure 1b is an exemplary block diagram of a video encoding and decoding system provided by an embodiment of the present application
  • Figure 2 is an exemplary block diagram of a video encoder provided by an embodiment of the present application.
  • Figure 3 is an exemplary block diagram of a video decoder provided by an embodiment of the present application.
  • Figure 4 is an exemplary schematic diagram of candidate image blocks provided by the embodiment of the present application.
  • Figure 5 is an exemplary block diagram of a video decoding device provided by an embodiment of the present application.
  • Figure 6 is an exemplary block diagram of a device provided by an embodiment of the present application.
  • Figure 7a is a schematic diagram of a system framework provided by an embodiment of the present application.
  • Figure 7b is a schematic diagram of probe distribution in a three-dimensional scene provided by an embodiment of the present application.
  • Figure 8a is a schematic diagram of a coding framework provided by an embodiment of the present application.
  • Figure 8b is a schematic structural diagram of a data format conversion module provided by an embodiment of the present application.
  • Figure 9a is a schematic diagram of a decoding framework provided by an embodiment of the present application.
  • Figure 9b is a schematic structural diagram of another data format conversion module provided by an embodiment of the present application.
  • Figure 10 is a schematic flow chart of an encoding method provided by an embodiment of the present application.
  • Figure 11 is a schematic flow chart of another encoding method provided by an embodiment of the present application.
  • Figure 12 is a schematic flowchart of a rendering loss determination method provided by an embodiment of the present application.
  • Figure 13 is a schematic flow chart of an encoding provided by an embodiment of the present application.
  • Figure 14 is a schematic flow chart of another encoding provided by an embodiment of the present application.
  • Figure 15 is a schematic flow chart of a decoding method provided by an embodiment of the present application.
  • Figure 16 is a schematic flow chart of another decoding method provided by an embodiment of the present application.
  • Figure 17 is a schematic structural diagram of a chip provided by an embodiment of the present application.
  • a and/or B can mean: A exists alone, A and B exist simultaneously, and they exist alone. B these three situations.
  • first and second in the description of the embodiments of the present application and the drawings are used to distinguish different objects, or to distinguish different processes on the same object, rather than to describe a specific order of objects. .
  • the reflection probe is a typical lighting probe. It records lighting data: the surrounding lighting conditions seen with the probe as the center. Its essence is data on the surface that is homeomorphic to the sphere. It can be spherical data or cube surface data, as shown in Figure 3.
  • the reflection probe is placed in the center of the metal sphere and bound to the metal sphere surface.
  • the algorithm calculates the exit angle, and then extracts the value corresponding to the exit angle from the data stored in the probe to obtain the picture that should be seen after reflection.
  • DDGI Dynamic diffuse global illumination
  • the probe body uses a probe volume composed of multiple probes. When the probe body is used to record lighting, it is also called a light field probe or irradiance volume. In addition, the probe body is also used in technologies such as precomputed radiance transfer.
  • each probe like the reflection probe, records illumination from various angles.
  • each probe also records visibility data, that is, the distribution data of the distance between objects at various angles and the probe. , including data such as the mean distance of each angle, the square of the distance, and the variance of the distance.
  • the storage method of DDGI data is as follows: a single probe is expanded into a square image in an octahedral expansion manner, and the images of multiple probes are arranged into a large image. In order to facilitate texture interpolation during use, a column of redundant boundary data is added to the top, bottom, left and right of each probe's square image.
  • Normalization in the compression of probe data, eliminates some invalid data by limiting the data range. During the compression, transmission and decompression process of probe data, whether and how normalization is performed will affect the rendering effect.
  • Preset maximum value normalization transform the data x into Among them, M is the preset maximum value, and data exceeding the maximum value will be truncated.
  • M can be a real number between 1 and 4.
  • M is the normalized parameter.
  • Maximum and minimum normalization transform the data x into Normalized to between [0,1].
  • the normalization parameters are max ⁇ x ⁇ and min ⁇ x ⁇ .
  • max ⁇ x ⁇ is the maximum value in data x
  • min ⁇ x ⁇ is the minimum value in data x.
  • Z-Score normalization transform the data x into in is the mean of x, and ⁇ is the standard deviation of x.
  • the normalization parameter is and ⁇ .
  • Data encoding and decoding includes two parts: data encoding and data decoding.
  • Data encoding is performed on the source side (or often referred to as the encoder side) and typically involves processing (e.g., compressing) the raw data to reduce the amount of data required to represent that raw data (and thus to store and/or transmit it more efficiently).
  • Data decoding is performed on the destination side (or commonly referred to as the decoder side) and typically involves inverse processing relative to the encoder side to reconstruct the original data.
  • the “coding” of data involved in the embodiments of this application should be understood as the “encoding” or “decoding” of data.
  • the encoding part and the decoding part are also collectively called the codec (encoding and decoding, CODEC).
  • lossless data encoding data can be reconstructed, that is, the reconstructed data has the same quality as the original data (assuming no transmission loss or other data loss during storage or transmission).
  • further compression is performed by quantization, etc., to reduce the amount of data required to represent the original data, and the decoder side cannot completely reconstruct the original data, that is, the quality of the reconstructed original data is lower than the quality of the original data or Difference.
  • the embodiments of this application can be applied to video data and other data with compression/decompression requirements.
  • the following uses the encoding of video data (referred to as video encoding) as an example to illustrate the embodiments of the present application.
  • video encoding For other types of data (such as image data, audio data, integer data, and other data with compression/decompression requirements), you can refer to the following description. , which will not be described again in the embodiments of this application.
  • the encoding process of audio data, integer data and other data does not need to be divided into blocks, but the data can be encoded directly.
  • Video coding generally refers to the processing of sequences of images that form a video or video sequence.
  • picture In the field of video coding, the terms “picture”, “frame” or “image” may be used as synonyms.
  • Video coding standards fall into the category of "lossy hybrid video codecs" (i.e., combining spatial and temporal prediction in the pixel domain with 2D transform coding in the transform domain to apply quantization).
  • Each image in a video sequence is typically split into a set of non-overlapping blocks, which are usually encoded at the block level.
  • the encoder usually processes i.e.
  • the encoder encodes the video at the block (video block) level, e.g., by spatial (intra) prediction and temporal (inter) prediction to produce the predicted block; from the current block (currently processed/to be processed block) to obtain the residual block; transform the residual block in the transform domain and quantize the residual block to reduce the amount of data to be transmitted (compressed), and the decoder side will perform the inverse processing relative to the encoder Partially applied to encoded or compressed blocks to reconstruct the current block used for representation. Additionally, the encoder needs to repeat the processing steps of the decoder so that the encoder and decoder generate the same predictions (eg, intra and inter prediction) and/or reconstruct pixels for processing, i.e. encoding subsequent blocks.
  • the encoder needs to repeat the processing steps of the decoder so that the encoder and decoder generate the same predictions (eg, intra and inter prediction) and/or reconstruct pixels for processing, i.e. encoding subsequent blocks.
  • FIG. 1a is an exemplary block diagram of a coding and decoding system 10 provided by an embodiment of the present application.
  • the video coding and decoding system 10 (or simply referred to as the coding and decoding system 10 ) can utilize the technology of the embodiment of the present application.
  • Video encoder 20 (or simply encoder 20 ) and video decoder 30 (or simply decoder 30 ) in video codec system 10 represent devices that may be used to perform various techniques according to the various examples described in the embodiments of this application. Equipment etc.
  • the encoding and decoding system 10 includes a source device 12 for providing encoded image data 21 such as encoded images to a destination device 14 for decoding the encoded image data 21 .
  • the source device 12 includes an encoder 20 and, additionally or optionally, an image source 16, a preprocessor (or preprocessing unit) 18 such as an image preprocessor, and a communication interface (or communication unit) 22.
  • Image source 16 may include or be any type of image capture device for capturing real-world images or the like, and/or any type of image generation device, such as a computer graphics processor or any type of user for generating computer animation images. Devices used to acquire and/or provide real-world images, computer-generated images such as screen content, virtual reality (VR) images, and/or any combination thereof (such as augmented reality (AR) images).
  • the image source may be any type of memory or storage that stores any of the above images.
  • the image (or image data) 17 may also be referred to as the original image (or original image data) 17.
  • the preprocessor 18 is used to receive the original image data 17 and perform preprocessing on the original image data 17 to obtain a preprocessed image (or preprocessed image data) 19 .
  • preprocessing performed by preprocessor 18 may include cropping, color format conversion (eg, from RGB to YCbCr), color grading, or denoising. It can be understood that the preprocessing unit 18 Can be an optional component.
  • Video encoder (or encoder) 20 is used to receive pre-processed image data 19 and provide encoded image data 21 (further described below with reference to FIG. 2 and the like).
  • the communication interface 22 in the source device 12 may be used to receive the encoded image data 21 and send the encoded image data 21 (or any other processed version) to another device such as the destination device 14 or any other device through the communication channel 13 for storage. Or rebuild directly.
  • the destination device 14 includes a decoder 30 and may additionally or optionally include a communication interface (or communication unit) 28, a post-processor (or post-processing unit) 32 and a display device 34.
  • the communication interface 28 in the destination device 14 is used to receive the encoded image data 21 (or any other processed version) directly from the source device 12 or from any other source device such as a storage device.
  • the storage device is an encoded image data storage device
  • the encoded image data 21 is provided to the decoder 30 .
  • Communication interface 22 and communication interface 28 may be used via a direct communication link between source device 12 and destination device 14, such as a direct wired or wireless connection, or the like, or via any type of network, such as a wired network, a wireless network, or any thereof.
  • the communication interface 22 may be used to encapsulate the encoded image data 21 into a suitable format such as a message, and/or process the encoded image data using any type of transmission encoding or processing for transmission over a communication link or network. transfer on.
  • the communication interface 28 corresponds to the communication interface 22 and can, for example, be used to receive transmission data and process the transmission data using any type of corresponding transmission decoding or processing and/or decapsulation to obtain the encoded image data 21 .
  • Both communication interface 22 and communication interface 28 may be configured as a one-way communication interface as indicated by the arrow pointing from the source device 12 to the corresponding communication channel 13 of the destination device 14 in Figure 1a, or as a bi-directional communication interface, and may be used to send and receive messages. etc., to establish the connection, confirm and exchange any other information related to the communication link and/or data transmission such as the transmission of encoded image data, etc.
  • the video decoder (or decoder) 30 is configured to receive encoded image data 21 and provide decoded image data (or decoded image data) 31 (further described below with reference to FIG. 3 and the like).
  • the post-processor 32 is used to perform post-processing on decoded image data 31 (also referred to as reconstructed image data) such as decoded images to obtain post-processed image data 33 such as post-processed images.
  • Post-processing performed by the post-processing unit 32 may include, for example, color format conversion (eg, from YCbCr to RGB), toning, cropping or resampling, or any other processing for generating decoded image data 31 for display by a display device 34 or the like. .
  • the display device 34 is used to receive the post-processed image data 33 to display the image to a user or viewer or the like.
  • Display device 34 may be or include any type of display for representing reconstructed images, such as an integrated or external display or display.
  • the display screen may include a liquid crystal display (LCD), an organic light emitting diode (OLED) display, a plasma display, a projector, a micro LED display, a liquid crystal on silicon display (LCoS) ), digital light processor (DLP) or any type of other display.
  • the encoding and decoding system 10 further includes a training engine 25 for training the encoder 20 (especially the entropy encoding unit 270 in the encoder 20) or the decoder 30 (especially the entropy decoding unit 304 in the decoder 30), Entropy encoding is performed on the image block to be encoded based on the estimated probability distribution.
  • a training engine 25 for training the encoder 20 (especially the entropy encoding unit 270 in the encoder 20) or the decoder 30 (especially the entropy decoding unit 304 in the decoder 30), Entropy encoding is performed on the image block to be encoded based on the estimated probability distribution.
  • training engine 25 for training the encoder 20 (especially the entropy encoding unit 270 in the encoder 20) or the decoder 30 (especially the entropy decoding unit 304 in the decoder 30), Entropy encoding is performed on the image block to be encoded based on the estimated probability distribution.
  • FIG. 1 a shows source device 12 and destination device 14 as separate devices
  • device embodiments may also include both source device 12 and destination device 14 or the functionality of both source device 12 and destination device 14 , that is, include both source devices 12 and 14 .
  • Device 12 or corresponding function and destination device 14 or corresponding function In these embodiments, source device 12 or corresponding functions and destination device 14 or corresponding functions may be implemented using the same hardware and/or software or by separate hardware and/or software or any combination thereof.
  • Figure 1b is an exemplary block diagram of the video encoding and decoding system 40 provided by the embodiment of the present application.
  • the encoder 20 (such as the video encoder 20) or the decoder 30 (such as the video decoder 30) or both All can be realized through the processing circuit in the video encoding and decoding system 40 as shown in Figure 1b, such as one or more microprocessors, digital signal processors (digital signal processors, DSPs), application-specific integrated circuits (application-specific integrated circuits) , ASIC), field-programmable gate array (FPGA), discrete logic, hardware, video encoding dedicated processor, or any combination thereof.
  • DSPs digital signal processors
  • ASIC application-specific integrated circuits
  • FPGA field-programmable gate array
  • Figure 2 is an exemplary block diagram of a video encoder provided by an embodiment of the present application
  • Figure 3 is an exemplary block diagram of a video decoder provided by an embodiment of the present application.
  • Encoder 20 may be implemented with processing circuitry 46 to include the various modules discussed with respect to encoder 20 of FIG. 2 and/or any other encoder system or subsystem described herein.
  • Decoder 30 may be implemented with processing circuitry 46 to include the various modules discussed with respect to decoder 30 of FIG. 3 and/or any other decoder system or subsystem described herein.
  • the processing circuitry 46 may be used to perform various operations discussed below.
  • the device can store the instructions of the software in a suitable non-transitory computer-readable storage medium, and use one or more processors to execute the instructions in hardware, thereby Implement the technology in the embodiments of this application.
  • One of video encoder 20 and video decoder 30 may be integrated in a single device as part of a combined encoder/decoder (CODEC), as shown in Figure 1b.
  • Source device 12 and destination device 14 may include any of a variety of devices, including any type of handheld or stationary device, such as a notebook or laptop computer, a cell phone, a smartphone, a tablet or tablet, a camera, Desktop computers, set-top boxes, televisions, display devices, digital media players, video game consoles, video streaming devices (e.g., content business servers or content distribution servers), broadcast receiving devices, broadcast transmitting devices, monitoring devices, etc., and It is possible to use no or any type of operating system.
  • the source device 12 and the destination device 14 may also be devices in a cloud computing scenario, such as virtual machines in a cloud computing scenario.
  • source device 12 and destination device 14 may be equipped with components for wireless communications. Accordingly, source device 12 and destination device 14 may be wireless communication devices.
  • the source device 12 and the destination device 14 can install virtual scene applications (applications, APPs) such as virtual reality (VR) applications, augmented reality (AR) applications, or mixed reality (MR) applications, and VR applications, AR applications or MR applications can be run based on user operations (such as click, touch, slide, shake, voice control, etc.).
  • the source device 12 and the destination device 14 can collect images/videos of any objects in the environment through cameras and/or sensors, and then display virtual objects on the display device based on the collected images/videos.
  • the virtual objects can be VR scenes, AR scenes, or Virtual objects in MR scenes (i.e. objects in the virtual environment).
  • the virtual scene applications in the source device 12 and the destination device 14 may be built-in applications of the source device 12 and the destination device 14 themselves, or may be third-party services installed by the users themselves. Applications provided by suppliers, there are no specific restrictions on this.
  • source device 12 and destination device 14 may install real-time video transmission applications, such as live broadcast applications.
  • the source device 12 and the destination device 14 can collect images/videos through cameras, and then display the collected images/videos on the display device.
  • the video encoding and decoding system 10 shown in FIG. 1a is only exemplary, and the technology provided by the embodiments of the present application may be applicable to video encoding settings (eg, video encoding or video decoding), which settings do not necessarily include encoding.
  • data is retrieved from local storage, sent over the network, and so on.
  • the video encoding device may encode the data and store the data in memory, and/or the video decoding device may retrieve the data from memory and decode the data.
  • encoding and decoding are performed by devices that do not communicate with each other but merely encode data to memory and/or retrieve and decode data from memory.
  • Figure 1b is an exemplary block diagram of a video coding and decoding system 40 provided by an embodiment of the present application.
  • the video coding and decoding system 40 may include an imaging device 41, a video encoder 20, a video decoding system processor 30 (and/or a video codec implemented by processing circuitry 46), antenna 42, one or more processors 43, one or more memory stores 44, and/or a display device 45.
  • the imaging device 41, the antenna 42, the processing circuit 46, the video encoder 20, the video decoder 30, the processor 43, the memory storage 44 and/or the display device 45 can communicate with each other.
  • video codec system 40 may include only video encoder 20 or only video decoder 30 .
  • antenna 42 may be used to transmit or receive an encoded bitstream of video data.
  • display device 45 may be used to present video data.
  • the processing circuit 46 may include application-specific integrated circuit (ASIC) logic, a graphics processor, a general-purpose processor, etc.
  • the video encoding and decoding system 40 may also include an optional processor 43, which may similarly include application-specific integrated circuit (ASIC) logic, a graphics processor, a general-purpose processor, etc.
  • the memory 44 may be any type of memory, such as volatile memory (eg, static random access memory (SRAM), dynamic random access memory (DRAM), etc.) or non-volatile memory. Volatile memory (for example, flash memory, etc.), etc.
  • memory store 44 may be implemented by cache memory.
  • processing circuitry 46 may include memory (eg, cache, etc.) for implementing image buffers, etc.
  • video encoder 20 implemented by logic circuitry may include an image buffer (eg, implemented by processing circuitry 46 or memory storage 44) and a graphics processing unit (eg, implemented by processing circuitry 46).
  • a graphics processing unit may be communicatively coupled to the image buffer.
  • the graphics processing unit may include video encoder 20 implemented with processing circuitry 46 to implement the various modules discussed with respect to FIG. 2 and/or any other encoder system or subsystem described herein.
  • Logic circuits can be used to perform the various operations discussed herein.
  • video decoder 30 may be implemented in a similar manner with processing circuitry 46 to implement the various aspects discussed with respect to video decoder 30 of FIG. 3 and/or any other decoder system or subsystem described herein. module.
  • logic circuitry implemented video decoder 30 may include an image buffer (implemented by processing circuitry 46 or memory storage 44 ) and a graphics processing unit (eg, implemented by processing circuitry 46 ).
  • a graphics processing unit may be communicatively coupled to the image buffer.
  • the graphics processing unit may include video decoder 30 implemented with processing circuitry 46 to implement the various modules discussed with respect to FIG. 3 and/or any other decoder system or subsystem described herein.
  • antenna 42 may be used to receive an encoded bitstream of video data.
  • the encoded bitstream may include data related to encoded video frames, indicators, index values, mode selection data, etc., as discussed herein, such as data related to encoded partitions (e.g., transform coefficients or quantized transform coefficients , optional indicators (as discussed, and/or data defining encoding splits).
  • Video codec system 40 may also include video decoder 30 coupled to antenna 42 and for decoding the encoded bitstream.
  • Display device 45 is used to present video frames.
  • video decoder 30 may be used to perform the opposite process.
  • video decoder 30 may be configured to receive and parse such syntax elements and decode related video data accordingly.
  • video encoder 20 may entropy encode the syntax elements into an encoded video bitstream.
  • video decoder 30 may parse such syntax elements and decode the associated video data accordingly.
  • VVC versatile video coding
  • VCEG ITU-T video coding experts group
  • MPEG ISO/IEC motion picture experts group
  • HEVC high-efficiency video coding
  • JCT-VC joint collaboration team on video coding
  • the video encoder 20 includes an input terminal (or input interface) 201, a residual calculation unit 204, a transformation processing unit 206, a quantization unit 208, an inverse quantization unit 210, an inverse transformation processing unit 212, and a reconstruction unit 214.
  • Loop filter 220 decoded picture buffer (decoded picture buffer, DPB) 230, mode selection unit 260, entropy encoding unit 270 and output terminal (or output interface) 272.
  • Mode selection unit 260 may include inter prediction unit 244, intra prediction unit 254, and segmentation unit 262.
  • Inter prediction unit 244 may include a motion estimation unit and a motion compensation unit (not shown).
  • the video encoder 20 shown in FIG. 2 may also be called a hybrid video encoder or a video encoder based on a hybrid video codec.
  • the inter prediction unit is a trained target model (also called a neural network), which is used to process an input image or image region or image block to generate a predicted value of the input image block.
  • a neural network for inter prediction is used to receive an input image or image region or image block and generate a predicted value for the input image or image region or image block.
  • the residual calculation unit 204, the transform processing unit 206, the quantization unit 208 and the mode selection unit 260 constitute the forward signal path of the encoder 20, while the inverse quantization unit 210, the inverse transform processing unit 212, the reconstruction unit 214, the buffer 216, the ring
  • the path filter 220, the decoded picture buffer (decoded picture buffer, DPB) 230, the inter prediction unit 244 and the intra prediction unit 254 form the backward signal path of the encoder, where the backward signal path of the encoder 20 corresponds to the decoding signal path of the decoder (see decoder 30 in Figure 3).
  • the inverse quantization unit 210 , the inverse transform processing unit 212 , the reconstruction unit 214 , the loop filter 220 , the decoded image buffer 230 , the inter prediction unit 244 and the intra prediction unit 254 also constitute the “built-in decoder” of the video encoder 20 .
  • the encoder 20 may be operable to receive images (or image data) 17 via an input 201 or the like, eg images in a sequence of images forming a video or video sequence.
  • the received image or image data may also be a pre-processed image (or pre-processed image data) 19 .
  • image 17 may also be called the current image or the image to be encoded (especially in video encoding when the current image is distinguished from other images, such as the same video sequence, that is, a video sequence that also includes the current image, previously encoded images and/or decoded images).
  • a (digital) image is or can be viewed as a two-dimensional array or matrix of pixels with intensity values.
  • the pixels in the array can also be called pixels (pixels or pels) (short for image elements).
  • the number of pixels in the array or image in the horizontal and vertical directions (or axes) determines the size and/or resolution of the image.
  • three color components are usually used, that is, the image can be represented as or include an array of three pixels.
  • an image includes an array of corresponding red, green, and blue pixels.
  • each pixel is usually represented in a luma/chroma format or color space, such as YCbCr, including a luma component indicated by Y (sometimes also represented by L) and two chroma components represented by Cb and Cr.
  • the luma component Y represents brightness or gray level intensity (for example, they are the same in a grayscale image), while the two chrominance (chroma) components Cb and Cr represent chrominance or color information components .
  • an image in the YCbCr format includes a brightness pixel array of brightness pixel values (Y) and two chroma pixel arrays of chroma values (Cb and Cr).
  • Images in RGB format can be converted or transformed into YCbCr format and vice versa, this process is also called color transformation or conversion. If the image is black and white, the image may only include an array of luminance pixels. Accordingly, the image may be, for example, a luminance pixel array in a monochrome format or an array of luminance pixels in a 4:2:0, 4:2:2 and 4:4:4 color format and two corresponding chrominance pixel arrays .
  • an embodiment of video encoder 20 may include an image segmentation unit (not shown in Figure 2) for segmenting image 17 into multiple (generally non-overlapping) image blocks 203. These blocks can also be called root blocks, macroblocks (H.264/AVC) or coding tree blocks (CTB), or coding tree units (CTUs) in the H.265/HEVC and VVC standards. ).
  • the segmentation unit can be used to use the same block size for all images in the video sequence and use a corresponding grid that defines the block size, or to vary the block size between images or subsets of images or groups of images and segment each image into corresponding piece.
  • the video encoder may be used to directly receive blocks 203 of image 17 , for example, one, a few, or all of the blocks that make up said image 17 .
  • the image block 203 may also be called a current image block or an image block to be encoded.
  • the image block 203 is also or can be considered as a two-dimensional array or matrix composed of pixel points with intensity values (pixel values), but the image block 203 is smaller than the image 17.
  • block 203 may include one array of pixels (eg, a luminance array in the case of a monochrome image 17 or a luminance array or a chrominance array in the case of a color image) or three arrays of pixels (eg, a luminance array in the case of a color image 17 one luminance array and two chrominance arrays) or any other number and/or type of arrays depending on the color format used.
  • the number of pixels in the horizontal and vertical directions (or axes) of the block 203 defines the size of the block 203 .
  • the block may be an M ⁇ N (M columns ⁇ N rows) pixel array, or an M ⁇ N transformation coefficient array, etc.
  • the video encoder 20 shown in Figure 2 is used to encode the image 17 on a block-by-block basis, eg, performing encoding and prediction on each block 203.
  • the video encoder 20 shown in FIG. 2 may also be used to segment and/or encode an image using slices (also referred to as video slices), where the image may use one or more slices (usually non-overlapping). ) to split or encode.
  • slices also referred to as video slices
  • Each slice may include one or more blocks (e.g., Coding Tree Units CTU) or one or more block groups (e.g., coding tiles in the H.265/HEVC/VVC standard and bricks (in the VVC standard) brick).
  • video encoder 20 shown in FIG. 2 may also be configured to use slice/encoding block groups (also referred to as video encoding block groups) and/or encoding blocks (also referred to as video encoding block groups). ) segment and/or encode an image, where the image may be segmented or encoded using one or more (usually non-overlapping) slice/coding block groups, each slice/coding block group may include one or more block (e.g. CTU) or one or more coding blocks, etc., where each coding A block may be in a shape such as a rectangle, and may include one or more complete or partial blocks (such as CTUs).
  • slice/encoding block groups also referred to as video encoding block groups
  • encoding blocks also referred to as video encoding block groups.
  • the residual calculation unit 204 is used to calculate the residual block 205 according to the image block (or original block) 203 and the prediction block 265 (the prediction block 265 will be introduced in detail later) in the following manner: for example, pixel by pixel (pixel by pixel) from the image
  • the pixel values of prediction block 265 are subtracted from the pixel values of block 203 to obtain the residual block 205 in the pixel domain.
  • the transformation processing unit 206 is used to perform discrete cosine transform (DCT) or discrete sine transform (DST) on the pixel values of the residual block 205 to obtain the transform coefficient 207 in the transform domain.
  • the transform coefficients 207 may also be called transform residual coefficients and represent the residual block 205 in the transform domain.
  • Transform processing unit 206 may be operable to apply an integerized approximation of DCT/DST, such as the transform specified for H.265/HEVC. Compared to the orthogonal DCT transform, this integer approximation is usually scaled by some factor. In order to maintain the norm of the residual blocks processed by forward and inverse transformations, additional scaling factors are used as part of the transformation process.
  • the scaling factor is usually chosen based on certain constraints, such as the scaling factor being a power of 2 used for the shift operation, the bit depth of the transform coefficients, the trade-off between accuracy and implementation cost, etc.
  • a specific scaling factor may be specified for the inverse transform on the encoder 20 side via the inverse transform processing unit 212 (and the corresponding inverse transform on the decoder 30 side via, for example, the inverse transform processing unit 312 ), and accordingly, a specific scaling factor may be specified at the encoder 20 On the side 20, a corresponding scaling factor is specified for the forward transformation through the transformation processing unit 206.
  • video encoder 20 may be configured to output transformation parameters such as one or more transformation types, for example, directly output or output after encoding or compression by entropy encoding unit 270 , for example, so that video decoder 30 can receive and use the transformation parameters for decoding.
  • transformation parameters such as one or more transformation types, for example, directly output or output after encoding or compression by entropy encoding unit 270 , for example, so that video decoder 30 can receive and use the transformation parameters for decoding.
  • the quantization unit 208 is configured to quantize the transform coefficient 207 by, for example, scalar quantization or vector quantization, to obtain a quantized transform coefficient 209.
  • the quantized transform coefficients 209 may also be called quantized residual coefficients 209.
  • the quantization process may reduce the bit depth associated with some or all transform coefficients 207. For example, n-bit transform coefficients may be rounded down to m-bit transform coefficients during quantization, where n is greater than m.
  • the degree of quantization can be modified by adjusting the quantization parameter (QP). For example, with scalar quantization, different degrees of scaling can be applied to achieve finer or coarser quantization. A smaller quantization step size corresponds to finer quantization, while a larger quantization step size corresponds to coarser quantization.
  • the appropriate quantization step size can be indicated by a quantization parameter (QP).
  • the quantization parameter may be an index into a predefined set of suitable quantization steps.
  • Quantization may include dividing by the quantization step size, and corresponding or inverse dequantization performed by inverse quantization unit 210 or the like may include multiplying by the quantization step size.
  • Embodiments according to some standards such as HEVC may be used to determine the quantization step size using quantization parameters.
  • the quantization step size can be calculated from the quantization parameters using a fixed-point approximation of the equation involving division.
  • Additional scaling factors can be introduced for quantization and dequantization to recover the norm of the residual block that may be modified due to the scaling used in the fixed-point approximation of the equations for quantization step size and quantization parameters.
  • the inverse transform and dequantized scales may be combined.
  • Quantization is a lossy operation, where the larger the quantization step size, the greater the loss.
  • video encoder 20 may be configured to output a quantization parameter (QP), for example, directly or after encoding or compression by entropy encoding unit 270
  • QP quantization parameter
  • the output allows video decoder 30 to receive and use the quantization parameters for decoding.
  • the inverse quantization unit 210 is configured to perform inverse quantization of the quantization unit 208 on the quantized coefficients to obtain the dequantized coefficients 211, for example, perform inverse quantization of the quantization scheme performed by the quantization unit 208 according to or using the same quantization step size as the quantization unit 208. plan.
  • the dequantized coefficient 211 may also be called the dequantized residual coefficient 211, which corresponds to the transform coefficient 207. However, due to losses caused by quantization, the inverse quantized coefficient 211 is usually not exactly the same as the transform coefficient.
  • the inverse transform processing unit 212 is configured to perform an inverse transform of the transform performed by the transform processing unit 206, such as an inverse discrete cosine transform (DCT) or an inverse discrete sine transform (DST), to perform a transformation in the pixel domain
  • DCT inverse discrete cosine transform
  • DST inverse discrete sine transform
  • a reconstructed residual block 213 (or corresponding dequantized coefficients 213) is obtained.
  • the reconstruction residual block 213 may also be called a transform block 213.
  • the reconstruction unit 214 (e.g., the summer 214) is used to add the transform block 213 (ie, the reconstruction residual block 213) to the prediction block 265 to obtain the reconstruction block 215 in the pixel domain, e.g., the reconstruction block 213
  • the pixel value is added to the pixel value of prediction block 265 .
  • the loop filter unit 220 (or simply "loop filter” 220) is used to filter the reconstruction block 215 to obtain the filter block 221, or is generally used to filter the reconstructed pixel points to obtain filtered pixel values.
  • loop filter units are used to smooth pixel transitions or improve video quality.
  • the loop filter unit 220 may include one or more loop filters, such as a deblocking filter, a sample-adaptive offset (SAO) filter, or one or more other filters, such as an automatic Adaptive loop filter (ALF), noise suppression filter (NSF), or any combination.
  • the loop filter unit 220 may include a deblocking filter, an SAO filter, and an ALF filter. The order of filtering process can be deblocking filter, SAO filter and ALF filter.
  • LMCS luma mapping with chroma scaling
  • SBT sub-block transform
  • ISP intra sub-partition
  • loop filter unit 220 is shown as a loop filter in FIG. 2, in other configurations, loop filter unit 220 may be implemented as a post-loop filter.
  • the filter block 221 may also be referred to as the filter reconstruction block 221.
  • video encoder 20 may be configured to output loop filter parameters (eg, SAO filter parameters, ALF filter parameters, or LMCS parameters), e.g., directly or by entropy
  • the encoding unit 270 performs entropy encoding and outputs it, for example, so that the decoder 30 can receive and use the same or different loop filter parameters for decoding.
  • Decoded picture buffer (DPB) 230 may be a reference picture memory that stores reference picture data for use by video encoder 20 when encoding video data.
  • DPB 230 may be formed from any of a variety of memory devices, such as dynamic random access memory (DRAM), including synchronous DRAM (SDRAM), magnetoresistive RAM (MRAM), Resistive RAM (RRAM) or other types of storage devices.
  • DRAM dynamic random access memory
  • SDRAM synchronous DRAM
  • MRAM magnetoresistive RAM
  • RRAM Resistive RAM
  • Decode image buffer The filter 230 may be used to store one or more filter blocks 221.
  • the decoded image buffer 230 may also be used to store other previous filtered blocks of the same current image or a different image such as a previous reconstructed image, such as the previously reconstructed and filtered block 221, and may provide the complete previous reconstructed, i.e., decoded image (and corresponding reference blocks and pixels) and/or a partially reconstructed current image (and corresponding reference blocks and pixels), for example for inter-frame prediction.
  • the decoded image buffer 230 may also be used to store one or more unfiltered reconstruction blocks 215, or generally store unfiltered reconstructed pixels, for example, the reconstruction blocks 215 that are not filtered by the loop filtering unit 220, or are not processed. Any other processed reconstruction blocks or reconstructed pixels.
  • Mode selection unit 260 includes segmentation unit 262, inter prediction unit 244, and intra prediction unit 254 for receiving or obtaining raw block 203 (current block 203 of current image 17) and reconstructed image data such as filtered and/or unfiltered reconstructed pixels of the same (current) image and/or one or more previously decoded images or Rebuild block.
  • the reconstructed image data is used as reference image data required for prediction such as inter-frame prediction or intra-frame prediction to obtain the prediction block 265 or the prediction value 265 .
  • Mode selection unit 260 may be used to determine or select a partitioning for the current block (including no partitioning) and prediction mode (eg, intra or inter prediction mode), generate a corresponding prediction block 265, and calculate the sum of residual block 205.
  • Reconstruction block 215 is performed.
  • mode selection unit 260 may be operable to select a segmentation and prediction mode (eg, from prediction modes supported or available by mode selection unit 260 ) that provides the best match or minimum residual (minimum Residual refers to better compression in transmission or storage), or provides minimum signaling overhead (minimum signaling overhead refers to better compression in transmission or storage), or considers or balances both of the above.
  • the mode selection unit 260 may be used to determine the segmentation and prediction modes according to rate distortion optimization (rate distortion Optimization, RDO), that is, select the prediction mode that provides minimum rate distortion optimization.
  • rate distortion optimization rate distortion Optimization
  • the segmentation unit 262 may be used to segment the images in the video sequence into a sequence of coding tree units (CTUs), and the CTUs 203 may be further segmented into smaller block parts or sub-blocks (again forming blocks), e.g. Iteratively use quad-tree partitioning (QT) partitioning, binary-tree partitioning (BT) partitioning, or triple-tree partitioning (TT) partitioning, or any combination thereof, and for example to block parts Or each of the sub-blocks performs prediction, where the mode selection includes selecting a tree structure of the partition block 203 and selecting a prediction mode applied to the block part or each of the sub-blocks.
  • QT quad-tree partitioning
  • BT binary-tree partitioning
  • TT triple-tree partitioning
  • Segmentation eg, performed by segmentation unit 262
  • prediction processing eg, performed by inter-prediction unit 244 and intra-prediction unit 254
  • the segmentation unit 262 may segment (or divide) one image block (or CTU) 203 into smaller parts, such as square or rectangular shaped tiles.
  • a CTU consists of N ⁇ N luminance pixel blocks and two corresponding chrominance pixel blocks.
  • the maximum allowed size of luma blocks in a CTU is specified as 128 ⁇ 128 in the developing versatile video coding (VVC) standard, but may be specified in the future as a value different from 128 ⁇ 128, such as 256 ⁇ 256.
  • VVC developing versatile video coding
  • the CTUs of an image can be grouped/grouped into slice/coded block groups, coded blocks or bricks.
  • a coding block covers a rectangular area of an image, and a coding block can be divided into one or more tiles.
  • a brick consists of multiple CTU lines within a coding block.
  • a coding block that is not divided into bricks can be called a brick.
  • bricks are a true subset of coded blocks and therefore are not called coded blocks.
  • VVC supports two encoding block group modes, namely raster scan slice/encoding block group mode and rectangular slice mode.
  • raster scan encoded block group mode a slice/encoded block group contains a sequence of encoded blocks in a raster scan of the image.
  • rectangular patch mode a patch contains multiple tiles of an image that together make up a rectangular area of the image.
  • the bricks within the rectangular piece are arranged in the order of the photo's brick raster scan.
  • These smaller blocks can be further divided into smaller parts.
  • This is also called tree splitting or hierarchical tree splitting, where a root block at root tree level 0 (hierarchy level 0, depth 0), etc. can be recursively split into two or more blocks at the next lower tree level, For example, a node at tree level 1 (hierarchy level 1, depth 1).
  • These blocks can in turn be split into two or more blocks at the next lower level, e.g. tree level 2 (hierarchy level 2, depth 2), etc., until the split ends (because the end criteria are met, e.g. maximum tree depth or minimum tree depth is reached) block size).
  • Blocks that are not further divided are also called leaf blocks or leaf nodes of the tree.
  • a tree divided into two parts is called a binary-tree (BT)
  • TT ternary-tree
  • QT quadtree
  • a Coding Tree Unit may be or include a CTB for a luma pixel, two corresponding CTBs for a chroma pixel in an image with three pixel arrays, or a CTB for a pixel in a monochrome image or use three separate
  • the color plane and syntax structure (used to encode the pixel) encode the CTB of the pixel of the image.
  • the coding tree block (CTB) can be an N ⁇ N pixel block, where N can be set to a certain value so that the components are divided into CTBs, which is segmentation.
  • a coding unit may be or include a coding block of luminance pixels, two corresponding coding blocks of chrominance pixels of an image with three pixel arrays, or a coding block of pixels of a monochrome image or use Coding blocks of pixels in an image encoded by three independent color planes and syntax structures (used to encode pixels).
  • the coding block can be a block of M ⁇ N pixels, where M and N can be set to a certain value such that the CTB is divided into coding blocks, which is segmentation.
  • a coding tree unit may be partitioned into multiple CUs according to HEVC using a quadtree structure represented as a coding tree.
  • the decision whether to encode an image region using inter (temporal) prediction or intra (spatial) prediction is made at the leaf CU level.
  • Each leaf CU can be further divided into one, two or four PUs according to the PU partition type.
  • the same prediction process is used within a PU, and relevant information is transmitted to the decoder in PU units.
  • the leaf CUs can be partitioned into transform units (TUs) according to other quadtree structures similar to the coding tree for the CU.
  • VVC Universal Video Coding
  • a combined quadtree of nested multi-type trees (such as binary trees and ternary trees) is used to partition for segmentation coding Segmented structure of the tree unit.
  • the CU can be square or rectangular.
  • the coding tree unit (CTU) is first divided by the quadtree structure.
  • the quadtree leaf nodes are further divided by multi-type Tree structure division.
  • Multi-type leaf nodes are called is a coding unit (CU), unless the CU is too large for the maximum transform length, such a segment is used for prediction and transform processing without any other segmentation. In most cases, this means that the CU, PU, and TU are in a quad
  • the block sizes in the coding block structure of tree-nested multi-type trees are the same. This exception occurs when the maximum supported transform length is less than the width or height of the color component of the CU.
  • VVC has formulated a quad-tree nested multi-type tree
  • the only signaling mechanism for partitioning information in the coding structure In the signaling mechanism, the coding tree unit (CTU) as the root of the quadtree is first divided by the quadtree structure. Then each quad leaf node (when large enough to be) is further split into a multi-type tree structure. In a multi-type tree structure, the first flag (mtt_split_cu_flag) is used to indicate whether the node is further divided.
  • CTU coding tree unit
  • mtt_split_cu_flag the first flag
  • the second flag (mtt_split_cu_vertical_flag) is first used to indicate the direction of division, and then the third flag (mtt_split_cu_binary_flag) is used to indicate whether the division is Binary tree partitioning or ternary tree partitioning.
  • the decoder can derive the multi-type tree split mode (MttSplitMode) of the CU based on predefined rules or tables.
  • TT division is not allowed. . TT division is also not allowed when the width or height of the chroma encoding block is greater than 32.
  • the pipeline design divides the image into multiple virtual pipeline data units (VPDU), and each VPDU is defined as a non-overlapping unit in the image.
  • VPDU size is roughly proportional to buffer size, so VPDUs need to be kept small.
  • the VPDU size can be set to the maximum transform block (TB) size.
  • TT ternary tree
  • BT binary tree
  • the tree node block is forced to be divided until all pixel points of each encoding CU are located within the image boundary.
  • the intra sub-partitions (ISP) tool can vertically or horizontally divide a luma intra prediction block into two or four sub-parts according to the block size.
  • mode selection unit 260 of video encoder 20 may be used to perform any combination of the segmentation techniques described above.
  • video encoder 20 is used to determine or select the best or optimal prediction mode from a (predetermined) set of prediction modes.
  • the set of prediction modes may include, for example, intra prediction modes and/or inter prediction modes.
  • the intra prediction mode set may include 35 different intra prediction modes, for example, non-directional modes like DC (or mean) mode and planar mode, or directional modes as defined by HEVC, or may include 67 different Intra prediction modes, for example, non-directional modes like DC (or mean) mode and planar mode, or directional modes as defined in VVC.
  • intra prediction modes for example, non-directional modes like DC (or mean) mode and planar mode, or directional modes as defined in VVC.
  • several traditional angle intra prediction modes are adaptively replaced by wide angle intra prediction modes for non-square blocks defined in VVC.
  • to avoid the division operation of DC prediction only the longer sides are used to calculate the average of non-square blocks.
  • the intra prediction results in planar mode can also be modified using the position-dependent intra prediction combination (PDPC) method.
  • PDPC position-dependent intra prediction combination
  • the intra prediction unit 254 is configured to generate an intra prediction block 265 using reconstructed pixel points of adjacent blocks of the same current image according to the intra prediction mode in the intra prediction mode set.
  • Intra-prediction unit 254 (or typically mode selection unit 260) is also operable to output intra-prediction parameters (or typically information indicating a selected intra-prediction mode for a block) to be sent to entropy encoding unit 270 in the form of syntax element 266 , to be included into the encoded image data 21 so that the video decoder 30 can perform operations such as receiving and using prediction parameters for decoding.
  • intra-prediction parameters or typically information indicating a selected intra-prediction mode for a block
  • the intra prediction modes in HEVC include DC prediction mode, plane prediction mode and 33 angle prediction modes, with a total of 35 candidate prediction modes.
  • the current block can be constructed using the pixels of the reconstructed image block to the left and above as a reference Intra prediction.
  • the image block in the surrounding area of the current block used for intra prediction of the current block becomes a reference block, and the pixels in the reference block are called reference pixels.
  • the DC prediction mode is suitable for areas with flat texture in the current block. All pixels in this area use the average value of the reference pixels in the reference block as prediction;
  • the plane prediction mode is suitable for image blocks with smooth changes in texture.
  • the current block that meets this condition uses the reference pixels in the reference block for bilinear interpolation as the prediction of all pixels in the current block;
  • the angle prediction mode takes advantage of the feature that the texture of the current block is highly correlated with the texture of the adjacent reconstructed image block , copy the value of the reference pixel in the corresponding reference block along a certain angle as the prediction of all pixels in the current block.
  • the HEVC encoder selects an optimal intra prediction mode from 35 candidate prediction modes for the current block, and writes the optimal intra prediction mode into the video code stream.
  • the encoder/decoder will derive the 3 most likely modes from the optimal intra prediction modes of the reconstructed image blocks using intra prediction in the surrounding area. If the current block is given The selected optimal intra prediction mode is one of the three most likely modes, then encoding a first index indicating that the selected optimal intra prediction mode is one of the three most likely modes; if selected The optimal intra prediction mode is not these 3 most likely modes, then a second index is encoded to indicate that the selected optimal intra prediction mode is the other 32 modes (except for the aforementioned 3 most likely modes among the 35 candidate prediction modes one of the other modes).
  • the HEVC standard uses a 5-bit fixed-length code as the aforementioned second index.
  • the method for the HEVC encoder to derive the three most likely modes includes: selecting the optimal intra prediction mode of the left adjacent image block and the upper adjacent image block of the current block and putting them into the set. If these two optimal intra prediction modes If they are the same, only one of them can be kept in the set. If the two optimal intra prediction modes are the same and both are angle prediction modes, then select two angle prediction modes adjacent to the angle direction to add to the set; otherwise, select the plane prediction mode, DC mode and vertical prediction mode in sequence. Join the set until the number of patterns in the set reaches 3.
  • the HEVC decoder After the HEVC decoder performs entropy decoding on the code stream, it obtains the mode information of the current block.
  • the mode information includes an indicator indicating whether the optimal intra prediction mode of the current block is among the three most likely modes, and the optimal intra prediction mode of the current block.
  • the set of inter prediction modes depends on the available reference pictures (i.e., for example at least part of the previously decoded pictures stored in the DBP 230) and other inter prediction parameters, for example on whether the entire reference picture or only the reference picture is used.
  • the best matching reference block is searched using a part of the reference image, e.g. a search window area near the area of the current block, and/or e.g. depending on whether half-pixel, quarter-pixel and/or sixteenth interpolation is performed pixel interpolation.
  • skip mode and/or direct mode may also be employed.
  • the merge candidate list of this mode consists of the following five candidate types in order: spatial MVP from spatially adjacent CUs, temporal MVP from collocated CUs, history-based MVP from FIFO table, pairwise Average MVP and zero MV.
  • Decoder side motion vector refinement based on bilateral matching can be used to increase the accuracy of the MV of the merge mode.
  • Merge mode with MVD comes from merge mode with motion vector differences. The MMVD flag is sent immediately after the skip flag and merge flag to specify whether the CU uses MMVD mode.
  • a CU-level adaptive motion vector resolution (AMVR) scheme can be used. AMVR supports CU's MVD encoding with different precisions.
  • a combined inter/intra prediction (CIIP) mode may be applied to the current CU.
  • the inter-frame and intra-frame prediction signals are weighted and averaged to obtain the CIIP prediction.
  • affine motion compensation prediction the affine motion field of a block is described by the motion information of 2 control point (4 parameters) or 3 control point (6 parameters) motion vectors.
  • Subblock-based temporal motion vector prediction (SbTMVP) is similar to temporal motion vector prediction (TMVP) in HEVC, but it predicts the motion of sub-CUs within the current CU. Vector.
  • Bi-directional optical flow (BDOF), formerly known as BIO, is a simplified version that reduces calculations, especially in terms of the number of multiplications and the size of the multipliers.
  • the CU In the triangle partition mode, the CU is evenly divided into two triangular parts using two division methods: diagonal division and anti-diagonal division. Additionally, the bidirectional prediction mode is extended beyond simple averaging to support weighted averaging of two prediction signals.
  • the inter prediction unit 244 may include a motion estimation (motion estimation, ME) unit and a motion compensation (motion compensation, MC) unit (both are not shown in FIG. 2).
  • the motion estimation unit may be operable to receive or acquire image block 203 (current image block 203 of current image 17 ) and decoded image 231 , or at least one or more previous reconstructed blocks, e.g. one or more other/different previously decoded images 231 Reconstruction blocks for motion estimation.
  • the video sequence may comprise the current image and the previous decoded image 231 or, in other words, the current image and the previous decoded image 231 may be part of or form a sequence of images forming the video sequence.
  • the encoder 20 may be operable to select a reference block from a plurality of reference blocks of the same or different images in a plurality of other images and assign the reference image (or reference image index) and/or the position (x, y coordinates) of the reference block to ) and the position of the current block (spatial offset) are provided to the motion estimation unit as inter prediction parameters.
  • This offset is also called a motion vector (MV).
  • the motion compensation unit is configured to obtain, for example, receive, inter prediction parameters, and perform inter prediction according to or use the inter prediction parameters to obtain the inter prediction block 246 .
  • Motion compensation performed by the motion compensation unit may include extracting or generating prediction blocks based on motion/block vectors determined through motion estimation, and may include performing interpolation to sub-pixel accuracy. Interpolation filtering can generate the pixels of other pixels from the pixels of known pixels, thereby potentially increasing the number of candidate prediction blocks that can be used to encode an image block.
  • the motion compensation unit may locate the prediction block pointed by the motion vector in one of the reference image lists.
  • the motion compensation unit may also generate syntax elements related to blocks and video slices for use by video decoder 30 when decoding the image blocks of the video slice.
  • sets of encoding blocks and/or encoding blocks and corresponding syntax elements may be generated or used.
  • the motion vector (motion vector, MV) that can be added to the candidate motion vector list as an alternative includes the spatial domain phase of the current block.
  • the MV of adjacent and temporally adjacent image blocks, where the MV of spatially adjacent image blocks may include the MV of the left candidate image block located to the left of the current block and the MV of the upper candidate image block located above the current block.
  • Figure 4 is an exemplary schematic diagram of candidate image blocks provided by an embodiment of the present application.
  • the set of candidate image blocks on the left includes ⁇ A0, A1 ⁇ , above
  • the set of candidate image blocks includes ⁇ B0, B1, B2 ⁇
  • the set of adjacent candidate image blocks in the time domain includes ⁇ C, T ⁇ . All three sets can be added to the candidate motion vector list as candidates, but According to existing coding standards, the maximum length of the candidate motion vector list of AMVP is 2, so it is necessary to determine the MV of up to two image blocks from the three sets according to the specified order to add to the candidate motion vector list.
  • the order may be to give priority to the set of candidate image blocks ⁇ A0, A1 ⁇ to the left of the current block.
  • the optimal MV is determined from the candidate motion vector list through the rate distortion cost (RD cost), and the candidate motion vector with the smallest RD cost is used as the motion vector prediction value (motion) of the current block. vector predictor, MVP).
  • the rate distortion cost is calculated by the following formula:
  • J represents RD cost
  • SAD is the sum of absolute differences (SAD) between the pixel value of the prediction block obtained after motion estimation using the candidate motion vector and the pixel value of the current block (sum of absolute differences, SAD)
  • R represents the code rate
  • ⁇ represents the Lagrange multiplier
  • the encoding end passes the determined MVP index in the candidate motion vector list to the decoding end. Furthermore, motion search can be performed in the neighborhood centered on the MVP to obtain the actual motion vector of the current block.
  • the encoding end calculates the motion vector difference (MVD) between the MVP and the actual motion vector, and converts the MVD into passed to the decoding end.
  • the decoder parses the index, finds the corresponding MVP in the candidate motion vector list based on the index, parses the MVD, and adds the MVD and MVP to obtain the actual motion vector of the current block.
  • the motion information that can be added to the candidate motion information list as an alternative includes the motion information of spatially adjacent or temporally adjacent image blocks of the current block, where the spatial domain Adjacent image blocks and temporally adjacent image blocks can be referred to Figure 4.
  • the candidate motion information corresponding to the spatial domain in the candidate motion information list comes from five spatially adjacent blocks (A0, A1, B0, B1 and B2). , if the adjacent block in the spatial domain is unavailable or is intra-frame predicted, its motion information will not be added to the candidate motion information list.
  • the candidate motion information in the time domain of the current block is obtained by scaling the MV of the corresponding position block in the reference frame according to the picture order count (POC) of the reference frame and the current frame.
  • POC picture order count
  • the block with position T in the reference frame is determined. Whether it is available, if not, select the block at position C.
  • the optimal motion information is determined from the candidate motion information list as the motion information of the current block through RD cost.
  • the encoding end transmits the index value (denoted as merge index) of the position of the optimal motion information in the candidate motion information list to the decoding end.
  • the entropy coding unit 270 is used to convert an entropy coding algorithm or scheme (for example, a variable length coding (VLC) scheme, a context adaptive VLC scheme (context adaptive VLC, CALVC), an arithmetic coding scheme, a binarization algorithm, Context adaptive binary arithmetic coding (CABAC), syntax-based context-adaptive binary arithmetic coding (SBAC), probability interval partitioning entropy (PIPE) ) coding or other entropy coding method or technique) is applied to the quantized residual coefficients 209, inter prediction parameters, intra prediction parameters, loop filter parameters and/or other syntax elements, resulting in an encoded bit stream that can be passed to the output 272
  • the encoded image data 21 output in the form of 21 or the like allows the video decoder 30 or the like to receive and use parameters for decoding.
  • the encoded bitstream 21 may be transmitted to the video decoder 30 or saved in memory for later transmission or retrieval by the video decoder
  • video encoder 20 may be used to encode video streams.
  • the non-transform based encoder 20 may directly quantize the residual signal without the transform processing unit 206 for certain blocks or frames.
  • encoder 20 may have quantization unit 208 and inverse quantization unit 210 combined into a single unit.
  • the video decoder 30 is configured to receive, for example, encoded image data 21 (eg, encoded bit stream 21 ) encoded by the encoder 20 to obtain a decoded image 331 .
  • the encoded image data or bitstream includes information for decoding said encoded image data, such as data representing image blocks of an encoded video slice (and/or a group of encoded blocks or encoded blocks) and associated syntax elements.
  • decoder 30 includes entropy decoding unit 304, inverse quantization unit 310, inverse transform processing unit 312, reconstruction unit 314 (eg, summer 314), loop filter 320, decoded image buffer 330, Mode application unit 360, inter prediction unit 344, and intra prediction unit 354.
  • Inter prediction unit 344 may be or include a motion compensation unit.
  • video decoder 30 may perform a decoding process that is generally inverse of the encoding process described with respect to video encoder 100 of FIG. 2 .
  • inverse quantization unit 210 may be functionally the same as the inverse quantization unit 110
  • the inverse transform processing unit 312 may be functionally the same as the inverse transform processing unit 122
  • the reconstruction unit 314 may be functionally the same as the reconstruction unit 214
  • the loop Filter 320 may be functionally identical to loop filter 220 and decoded image buffer 330 may be functionally identical to decoded image buffer 230. Accordingly, explanations of the corresponding units and functions of video encoder 20 apply accordingly to the corresponding units and functions of video decoder 30 .
  • the entropy decoding unit 304 is used to parse the bit stream 21 (or generally encoded image data 21) and perform entropy decoding on the encoded image data 21 to obtain quantization coefficients 309 and/or decoded encoding parameters (not shown in Figure 3), etc. , such as in inter prediction parameters (such as reference picture index and motion vector), intra prediction parameters (such as intra prediction mode or index), transformation parameters, quantization parameters, loop filter parameters and/or other syntax elements, etc. Any or all.
  • the entropy decoding unit 304 may be configured to apply a decoding algorithm or scheme corresponding to the encoding scheme of the entropy encoding unit 270 of the encoder 20 .
  • Entropy decoding unit 304 may also be used to provide inter prediction parameters, intra prediction parameters, and/or other syntax elements to mode application unit 360 , as well as other parameters to other units of decoder 30 .
  • Video decoder 30 may receive syntax elements at the video slice and/or video block level. In addition, or instead of slices and corresponding syntax elements, groups of encoding blocks and/or encoding blocks and corresponding syntax elements may be received or used.
  • Inverse quantization unit 310 may be configured to receive a quantization parameter (QP) (or generally information related to inverse quantization) and quantization coefficients from encoded image data 21 (eg, parsed and/or decoded by entropy decoding unit 304), and based on The quantization parameter inversely quantizes the decoded quantization coefficient 309 to obtain an inverse quantization coefficient 311, which may also be called a transform coefficient 311.
  • QP quantization parameter
  • the inverse quantization process may include using quantization parameters calculated by video encoder 20 for each video block in the video slice to determine the degree of quantization, as well as the degree of inverse quantization that needs to be performed.
  • the inverse transform processing unit 312 may be configured to receive the dequantized coefficients 311, also referred to as transform coefficients 311, and apply a transform to the dequantized coefficients 311 to obtain a reconstructed residual block 213 in the pixel domain.
  • the reconstruction residual block 213 may also be referred to as the transform block 313.
  • the transform may be an inverse transform, such as an inverse DCT, an inverse DST, an inverse integer transform, or a conceptually similar inverse transform process.
  • Inverse transform processing unit 312 may also be used to parse and/or decode data from encoded image data 21 (eg, by entropy decoding unit 304 code) receives the transform parameters or corresponding information to determine the transform to be applied to the dequantized coefficients 311.
  • the reconstruction unit 314 (for example, the summer 314) is used to add the reconstruction residual block 313 to the prediction block 365 to obtain the reconstruction block 315 in the pixel domain, for example, the pixel point value of the reconstruction residual block 313 and the prediction block 365 pixel values are added together.
  • the loop filter unit 320 (in or after the encoding loop) is used to filter the reconstruction block 315 to obtain the filter block 321, thereby smoothly performing pixel conversion or improving video quality.
  • the loop filter unit 320 may include one or more loop filters, such as a deblocking filter, a sample-adaptive offset (SAO) filter, or one or more other filters, such as an automatic Adaptive loop filter (ALF), noise suppression filter (NSF), or any combination.
  • the loop filter unit 220 may include a deblocking filter, an SAO filter, and an ALF filter. The order of filtering process can be deblocking filter, SAO filter and ALF filter.
  • LMCS luma mapping with chroma scaling
  • SBT sub-block transform
  • ISP intra sub-partition
  • loop filter unit 320 is shown in FIG. 3 as a loop filter, in other configurations, loop filter unit 320 may be implemented as a post-loop filter.
  • the decoded video blocks 321 in one image are then stored in a decoded image buffer 330, which stores the decoded image 331 as a reference image for subsequent motion compensation of other images and/or respective output displays.
  • the decoder 30 is used to output the decoded image 311 through the output terminal 312 and so on, for display to the user or for the user to view.
  • Inter prediction unit 344 may be functionally the same as inter prediction unit 244 (especially a motion compensation unit), and intra prediction unit 354 may be functionally the same as inter prediction unit 254 and is based on coded image data 21 (e.g., The partitioning and/or prediction parameters or corresponding information received by the entropy decoding unit 304 (parsed and/or decoded) determine the partitioning or partitioning and perform prediction.
  • the mode application unit 360 may be configured to perform prediction (intra-frame or inter-frame prediction) of each block according to the reconstructed image, block or corresponding pixel point (filtered or unfiltered) to obtain the prediction block 365.
  • intra prediction unit 354 in mode application unit 360 is used to generate a block based on the indicated intra prediction mode and data from previously decoded blocks of the current image.
  • inter prediction unit 344 eg, motion compensation unit
  • inter prediction unit 344 eg, motion compensation unit
  • Element generates prediction blocks 365 for video blocks of the current video slice. For inter prediction, these prediction blocks may be generated from one of the reference pictures in one of the reference picture lists.
  • Video decoder 30 may construct reference frame list 0 and list 1 using a default construction technique based on the reference images stored in DPB 330 .
  • the same or similar process may be applied to embodiments of encoding blocks (e.g., video encoding blocks) and/or encoding blocks (e.g., video encoding blocks) in addition to slices (e.g., video slices) or as an alternative to slices,
  • video may be encoded using I, P or B encoding block groups and/or encoding blocks.
  • the mode application unit 360 is configured to determine prediction information for a video block of the current video slice by parsing the motion vector and other syntax elements, and use the prediction information to generate a prediction block for the current video block being decoded. For example, mode application unit 360 uses some of the received syntax elements to determine a prediction mode (eg, intra prediction or inter prediction) for encoding a video block of the video slice, an inter prediction slice type (eg, B slice, P slice, or GPB slice), construction information for one or more reference picture lists for the slice, motion vectors for each inter-coded video block of the slice, inter-prediction status for each inter-coded video block of the slice, Other information to decode video blocks within the current video slice.
  • a prediction mode eg, intra prediction or inter prediction
  • an inter prediction slice type eg, B slice, P slice, or GPB slice
  • construction information for one or more reference picture lists for the slice motion vectors for each inter-coded video block of the slice, inter-prediction status for each inter-coded video block of
  • encoding blocks e.g., video encoding blocks
  • encoding blocks e.g., video encoding blocks
  • encoding blocks e.g., video encoding blocks
  • slices e.g., video slices
  • video may be encoded using I, P or B encoding block groups and/or encoding blocks.
  • video encoder 30 of Figure 3 may also be used to segment and/or decode images using slices (also called video slices), where the image may be made using one or more slices (typically non-overlapping) Split or decode.
  • slices also called video slices
  • Each slice may include one or more blocks (eg, CTUs) or one or more block groups (eg, encoded blocks in the H.265/HEVC/VVC standard and bricks in the VVC standard).
  • the video decoder 30 shown in FIG. 3 may also be configured to use slice/encoding block groups (also referred to as video encoding block groups) and/or encoding blocks (also referred to as video encoding blocks). ) to segment and/or decode an image, where the image may be segmented or decoded using one or more (usually non-overlapping) slice/coding block groups, each of which may include one or more block (eg, CTU) or one or more coding blocks, etc., wherein each coding block may be in a shape such as a rectangle, and may include one or more complete or partial blocks (eg, CTU).
  • slice/encoding block groups also referred to as video encoding block groups
  • encoding blocks also referred to as video encoding blocks.
  • video decoder 30 may be used to decode encoded image data 21 .
  • decoder 30 may generate the output video stream without loop filter unit 320.
  • the non-transform based decoder 30 may directly inverse-quantize the residual signal without the inverse-transform processing unit 312 for certain blocks or frames.
  • video decoder 30 may have inverse quantization unit 310 and inverse transform processing unit 312 combined into a single unit.
  • the processing result of the current step can be further processed and then output to the next step.
  • further operations such as clipping or shifting, can be performed on the processing results of interpolation filtering, motion vector derivation or loop filtering.
  • the value of the motion vector is limited to a predefined range based on the representation bit of the motion vector. If the representation bit of the motion vector is bitDepth, the range is -2 ⁇ (bitDepth-1) to 2 ⁇ (bitDepth-1)-1, where " ⁇ " represents a power. For example, if bitDepth is set to 16, the range is -32768 ⁇ 32767; if bitDepth is set to 18, the range is -131072 ⁇ 131071.
  • the values for deriving motion vectors are restricted such that the maximum difference between the integer parts of the MVs of the four 4x4 sub-blocks is not More than N pixels, such as no more than 1 pixel.
  • Two methods of limiting motion vectors based on bitDepth are provided here.
  • codec system 10 encoder 20, and decoder 30, as well as other embodiments described herein, may also be used for still image processing or codecs. That is, the processing or coding of a single image in a video codec that is independent of any previous or consecutive images.
  • inter prediction unit 244 encoder
  • inter prediction unit 344 decoder
  • All other functions (also called tools or techniques) of video encoder 20 and video decoder 30 are also Can be used for static image processing such as residual calculation 204/304, transform 206, quantization 208, inverse quantization 210/310, (inverse) transform 212/312, segmentation 262/362, intra prediction 254/354 and/or looping Filtering 220/320, entropy encoding 270 and entropy decoding 304.
  • FIG. 5 is an exemplary block diagram of a video decoding device 500 provided by an embodiment of the present application.
  • Video coding device 500 is suitable for implementing the disclosed embodiments described herein.
  • the video decoding device 500 may be a decoder, such as the video decoder 30 in FIG. 1a, or an encoder, such as the video encoder 20 in FIG. 1a.
  • the video decoding device 500 includes: an inlet port 510 (or input port 510) for receiving data and a receiving unit (receiver unit, Rx) 520; a processor, logic unit or central processing unit (central processing unit) for processing data , CPU) 530; for example, the processor 530 here can be a neural network processor 530; a transmitter unit (Tx) 540 for transmitting data and an output port 550 (or output port 550); for storing data Memory 560.
  • the video decoding device 500 may further include optical-to-electrical (OE) components and electrical-to-optical (EO) components coupled to the inlet port 510, the receiving unit 520, the transmitting unit 540, and the egress port 550, An outlet or entrance for optical or electrical signals.
  • OE optical-to-electrical
  • EO electrical-to-optical
  • Processor 530 is implemented in hardware and software.
  • Processor 530 may be implemented as one or more processor chips, cores (eg, multi-core processors), FPGAs, ASICs, and DSPs.
  • Processor 530 communicates with ingress port 510, receiving unit 520, transmitting unit 540, egress port 550, and memory 560.
  • Processor 530 includes a decoding module 570 (eg, a neural network-based decoding module 570).
  • Decoding module 570 implements the embodiments disclosed above. For example, decoding module 570 performs, processes, prepares, or provides various encoding operations. Therefore, the decoding module 570 provides a substantial improvement in the functionality of the video decoding device 500 and affects the switching of the video decoding device 500 to different states.
  • decoding module 570 may be implemented as instructions stored in memory 560 and executed by processor 530 .
  • Memory 560 includes one or more disks, tape drives, and solid-state drives that may be used as overflow data storage devices to store programs when they are selected for execution, and to store instructions and data that are read during program execution.
  • Memory 560 may be volatile and/or non-volatile, and may be read-only memory (ROM), random access memory (RAM), ternary content-addressable memory (ternary content-addressable memory (TCAM) and/or static random-access memory (static random-access memory (SRAM)).
  • ROM read-only memory
  • RAM random access memory
  • TCAM ternary content-addressable memory
  • SRAM static random-access memory
  • Figure 6 is an exemplary block diagram of a device 600 provided by an embodiment of the present application.
  • the device 600 can be used as either or both of the source device 12 and the destination device 14 in Figure 1a.
  • Processor 602 in device 600 may be a central processing unit.
  • processor 602 may be any other type of device or devices that exists or may be developed in the future that is capable of manipulating or processing information.
  • the disclosed implementations may be implemented using a single processor, such as processor 602 as shown, it is faster and more efficient to use more than one processor.
  • memory 604 in apparatus 600 may be a read-only memory (ROM) device or a random access memory (RAM) device. Any other suitable type of storage device may be used as memory 604.
  • Memory 604 may include code and data 606 that processor 602 accesses via bus 612 .
  • Memory 604 may also include an operating system 608 and application programs 610 including at least one program that allows processor 602 to perform the methods described herein.
  • applications 610 may include Applications 1-N, and also include a video coding application that performs the methods described herein.
  • Apparatus 600 may also include one or more output devices, such as display 618.
  • display 618 may be a touch-sensitive display that combines a display with a touch-sensitive element that can be used to sense touch input.
  • Display 618 may be coupled to processor 602 via bus 612 .
  • bus 612 in device 600 is described herein as a single bus, bus 612 may include multiple buses. Additionally, auxiliary storage may be directly coupled to other components of device 600 or accessed through a network, and may include a single integrated unit, such as a memory card, or multiple units, such as multiple memory cards. Accordingly, device 600 may have a wide variety of configurations.
  • the encoding and decoding methods provided by the embodiments of this application can be applied to various encoding and decoding scenarios.
  • the encoding and decoding method provided by the embodiment of the present application can be applied to a scene where N terminals (that is, N devices) are collaboratively rendered, where N is an integer greater than 1.
  • one device can generate rendering input information (rendering input information can include one of three-dimensional object models (also called 3D (3-dimension, three-dimensional) object models), probe data, etc.
  • rendering input information can include one of three-dimensional object models (also called 3D (3-dimension, three-dimensional) object models), probe data, etc.
  • the embodiment of the present application does not limit this; the embodiment of the present application takes rendering the input information as probe data as an example for illustration), and then distributes the probe data to other N-1 devices.
  • the coloring effect of the objects in the three-dimensional scene (corresponding to the three-dimensional object model) can be determined based on the probe data during the rendering process; after the rendering is completed, the rendered image can be obtained .
  • probe data can be generated collaboratively by N1 (the value of N1 ranges from 2 to N, where N1 can be equal to 2 or N, and N1 is an integer) devices, where each of the N1 devices A portion of the probe data generated by the device. Then, each of the N1 devices distributes part of the probe data generated by itself to the other N-1 devices.
  • N1 devices receive the probe data, during the rendering process, they can determine the coloring effect of the objects in the three-dimensional scene based on the received probe data and part of the probe data generated by themselves; after the rendering is completed, you can get The rendered image.
  • N-N1 devices receive the probe data, during the rendering process, the coloring effect of the objects in the three-dimensional scene can be determined based on the received probe data; after the rendering is completed, the rendered image can be obtained.
  • the device that generates probe data in the N-side collaborative rendering scene can be called the first device. It will be used for rendering and determine the coloring effect of objects in the three-dimensional scene based on the probe data during the rendering process. It is called the second device; a device can be either the first device or the second device, and this application does not limit this.
  • the first device may be a server or a terminal; the second device may be a terminal.
  • Figure 7a is a schematic diagram of an exemplary system framework.
  • the first device is a computing center server deployed in the cloud
  • the second device is a client.
  • Figure 7a is a schematic diagram of the framework of a device-cloud collaborative rendering system exemplarily shown.
  • the device-cloud collaborative rendering system may include: a computing center server, an edge server, and a client; wherein, the edge server may include n (n is an integer greater than 1), and the client may include k1+k2+ ...+kn, k1, k2...kn, are all positive integers.
  • the computing center server is connected to n edge servers, and each edge server is connected to at least one client.
  • edge server 1 is connected to k1 clients including client 11, client 12,..., client k1, and edge server 2 is connected to client 21, client 22,... ..., client k2, k2 clients are connected, ..., edge server n is connected with client n1, client n2, ..., client kn, kn clients.
  • the computing center server may be a server or a server cluster, which is not limited in the embodiment of the present application.
  • the embodiment of the present application does not limit the number n of edge servers, which can be set according to actual application scenarios.
  • the embodiment of the present application does not limit this.
  • the embodiment of the present application does not limit the number of clients connected to each edge server, which can be set according to actual application scenarios.
  • the number of clients connected to each edge server can be the same or different (that is, k1, k2...kn can be equal or unequal), and can be set according to the actual application scenario.
  • This application implements There is no restriction on this.
  • the client may include but is not limited to: personal computers, mobile phones, VR (Virtual Reality, virtual reality) wearable devices and other terminal devices.
  • VR Virtual Reality, virtual reality
  • the device-cloud collaborative rendering system framework shown in Figure 7a is only an example of the device-cloud collaborative rendering system framework according to the embodiment of the present application.
  • the computing center server and the edge server It can be the same server; or the device-cloud collaborative rendering system in the embodiment of the present application does not include an edge server, but the computing center server is connected to each client.
  • the embodiment of the present application does not limit this.
  • This embodiment of the present application takes the device-cloud collaborative rendering system framework shown in Figure 7a as an example for illustrative explanation.
  • a computing center server can be used to generate probe data.
  • edge servers can be used to distribute probe data.
  • the client can be used to render and display the rendered image; during the rendering process, the coloring effect of the object in the three-dimensional scene can be determined based on the probe data.
  • multi-device collaborative rendering scenarios such as cloud games, cloud exhibitions, interior decoration, clothing design, and architectural design can all be implemented using the device-cloud collaborative rendering system framework shown in Figure 7a.
  • the computing center server can generate probe data corresponding to the game scene from the target perspective; and then send the probe data to the edge server 1, and the edge server 1 will The probe data is sent to client 11.
  • the client 11 can render, and during the rendering process, according to the received probe data, determine the coloring effect of the object in the game scene corresponding to the target perspective; after the rendering is completed, the game scene corresponding to the target perspective can be obtained image and displayed.
  • the computing center server can generate probe data corresponding to the living room scene after adding the target furniture; and then send the probe data to the edge server 2.
  • the edge server 2 sends the probe data to the client 21 .
  • the client 21 can render, and during the rendering process, according to the received probe data, determine the coloring effect of the objects in the living room scene after adding the target furniture; after the rendering is completed, the added target furniture can be obtained The living room image after that is displayed.
  • the following introduces the process of the computing center server generating probe data, and the process of the client determining the coloring effect of objects in the three-dimensional scene based on the probe data during the rendering process.
  • the rendering process of the computing center server can be as follows: load a three-dimensional object model (which can include a human model or an object model) into a three-dimensional scene (which can also be called a 3D scene) (in this way, the three-dimensional object model can be converted into Objects in the three-dimensional scene), and then the objects in the three-dimensional scene can be rendered to obtain the current frame (that is, the rendered image).
  • a three-dimensional object model which can include a human model or an object model
  • the three-dimensional object model can be converted into Objects in the three-dimensional scene
  • the objects in the three-dimensional scene can be rendered to obtain the current frame (that is, the rendered image).
  • multiple probes can be placed in the three-dimensional scene during the rendering process of the objects in the three-dimensional scene, and the probes can be used to detect the surrounding environment.
  • Figure 7b is a schematic diagram of probe distribution in a three-dimensional scene. Each small ball in Figure 7b represents a probe. In the embodiment of Figure 7b, the probe is a DDGI probe.
  • the position of each probe in the three-dimensional scene and the positional relationship between each probe and other probes can be set according to requirements, and the embodiment of the present application does not limit this.
  • the distance between each probe and the six probes in the six directions around it is equal.
  • the number of probes placed in the three-dimensional scene can also be set according to requirements, and the embodiments of the present application do not limit this.
  • the attribute data includes but is not limited to: the type of probe (such as reflection probe, DDGI probe), the activation identifier of the probe, the position of the probe, and the position offset of the probe (for example, placed in a preset manner)
  • the initial position of each probe can be obtained; in order to obtain better coloring effects, the positions of some probes can be adjusted; in this way, for these probes, the offset between the adjusted position and the initial position can be It is called the position offset of the probe.
  • the distance between each probe and the six surrounding probes is equal; if the position of a certain probe is adjusted, the distance between the probe and the six probes around it will be equal. The distance between the probe and the six surrounding probes is not equal), etc.; this application does not limit this.
  • each probe can detect the surrounding environment centered on itself, that is, detect the characteristics of surrounding objects centered on itself in the three-dimensional scene, and record these characteristics.
  • the surrounding environment data includes at least one of lighting data, color, visibility data, material, normal direction or texture coordinates.
  • Illumination data can be used to describe the outgoing illumination of objects around the probe. Visibility data is the distribution data of the distance between objects at various angles and the probe, including the mean of the distance at each angle, the square of the distance and the variance of the distance, etc. data.
  • the DDGI algorithm can be used to generate lighting data and visibility data corresponding to each probe.
  • the following takes a probe of the current frame as an example to explain the process of generating the lighting data and visibility data of the probe. .
  • First sample several rays emitted from the probe, and calculate the first intersection point between these rays and each object in the three-dimensional scene. Then, calculate the distance between each of the several rays of the probe and the first intersection point of each object in the three-dimensional scene to obtain the initial distance data; and calculate the distance between each object in the three-dimensional scene and each of the several rays.
  • the illumination of the first intersection point is used to obtain the initial illumination data.
  • the initial distance data can be converted from the discrete domain to the spherical data in the continuous domain.
  • the cos ⁇ k kernel function (k is a positive integer) can be used on the spherical surface to filter the initial distance data to obtain candidates. distance data.
  • the initial distance data can be converted from the discrete domain to the spherical data in the continuous domain.
  • the cos ⁇ k kernel function (k is a positive integer) can be used on the spherical surface to filter the square of the initial distance data to Get the square of the candidate distance data.
  • the initial illumination data can be converted from the discrete domain to the spherical data in the continuous domain.
  • the cos ⁇ k kernel function (k is a positive integer) can be used on the spherical surface to filter the initial illumination data to obtain candidate illumination. data. Then, the candidate distance data of the probe is weighted with the distance data of the probe in the previous frame to obtain the distance data of the probe in the current frame; the square of the candidate distance data of the probe is summed with the above Perform a weighted calculation on the square of the distance data of the probe in one frame to obtain the square of the distance data of the probe in the current frame; and compare the candidate illumination data of the probe with the illumination data of the probe in the previous frame. Weighted calculation is performed to obtain the illumination data of the probe in the current frame. In this way, the lighting data and visibility data of all probes in the current frame can be obtained.
  • the attribute data and environment data used in the rendering process may constitute the probe data of the probe.
  • the illumination data and visibility data of each probe can be represented by a two-dimensional image, a spherical harmonic function base coefficient, or a spherical wavelet base coefficient, which is not limited by this application.
  • M is a positive integer
  • M1 probes have any one of illumination data, visibility data and attribute data
  • M2 probes have illumination data. Any two data among data, visibility data and attribute data
  • M3 probes have illumination data, visibility data and attribute data
  • M4 probes do not have probe data.
  • M1+M2+M3+M4 M
  • M1, M2, M3 and M1 are all integers. The values of M1, M2, M3 and M4 can be set according to the requirements, and the embodiment of the present application does not limit this.
  • the client determines the coloring effect of objects in the three-dimensional scene based on probe data:
  • probe data will be used to calculate the shading effect of objects in the three-dimensional scene. Specifically, when rendering each pixel, first obtain the coordinates of the 3D space corresponding to the pixel, and then find the 8 probes surrounding the coordinates. Next, calculate the contribution weight of each probe to the pixel through the visibility data of the probe, that is, judge whether the probe and its 3D coordinates are visible to each other through the distance. If not, the weight is 0. If it is visible, then pass The square of the distance calculates the contribution weight of the probe. After that, the contribution weight is used to perform a weighted average of the lighting data of the probe to obtain the shading result of the pixel.
  • the computing center server can compress the probe data before sending it to the client to reduce network bandwidth.
  • Figure 8a is a schematic diagram of an exemplary coding framework.
  • the encoder may include: a code stream load balancing module, a data form conversion module, a first rearrangement module and an encoding module.
  • the code stream load balancing module can be used to determine the target code rate and coding method (such as intra-frame coding or inter-frame coding) of the probe data.
  • the data form conversion module can be used to convert the environment data into a data form to convert the environment data into a more compact representation; or to increase the occupation of more important data required by the rendering process in the code stream. number of bits.
  • the first rearrangement module may be used to rearrange the attribute data of the probe.
  • the attribute data of the probe may include attribute data used for data form conversion (hereinafter referred to as first attribute data), and the above-mentioned attribute data used in the rendering process (hereinafter referred to as second attribute data).
  • first attribute data attribute data used for data form conversion
  • second attribute data attribute data used in the rendering process
  • the encoding module is used for encoding to obtain a code stream.
  • the steps performed by the code stream load balancing module, the data format conversion module and the first rearrangement module belong to the steps in the encoder encoding process.
  • FIG. 8a is only an example of the encoder of the embodiment of the present application, and the encoder of the embodiment of the present application may have fewer modules than that of FIG. 8a.
  • the encoder includes: a code stream load balancing module, a data form conversion module and an encoding module; for another example, the encoder includes: a data form conversion module, a first rearrangement module and an encoding module; for another example, the encoder includes: a data Form conversion module and encoding module; etc.
  • the encoder in the embodiment of the present application may have more modules than in Figure 8a, and the embodiment of the present application does not limit this.
  • code stream load balancing module, data format conversion module, first rearrangement module and encoding module in Figure 8a can be independent modules, or any two or more modules among them can be one Overall, the embodiments of this application do not limit this.
  • code stream load balancing module, data form conversion module, first rearrangement module and encoding module are logical modules.
  • the encoder can also be divided into other modules or these modules adopt other names. The embodiments of the present application do not limit this.
  • the encoder only includes the encoding module, the code stream load balancing module, the data format conversion module and the first rearrangement module, which can be independent of the encoder, and the embodiments of the present application do not limit this.
  • This embodiment of the present application takes the encoder in Figure 8a as an example for illustrative description.
  • Figure 8b is a schematic structural diagram of an exemplary data format conversion module.
  • the data form conversion module may include: a quantization module, a domain conversion module and a second rearrangement module.
  • a quantization module can be used for quantization.
  • a domain conversion module can be used for domain conversion.
  • domain conversion may refer to converting a representation of data from one domain to another domain.
  • domains can be divided from different angles according to needs, for example:
  • normalized domain From the perspective of whether it is normalized, it can be divided into: normalized domain and non-normalized domain.
  • RGB domain From the perspective of color space, it can be divided into: RGB domain, YUV domain, XYZ domain and Lab domain.
  • the nonlinear domain can be such as exponential domain, PQ (Perceptual Quantization, perceptual quantization) domain, HLG (Hybird log gamma, hybrid log gamma) ) domain, etc.
  • the image domain may refer to a domain represented by images.
  • the transformation domain can refer to a domain represented by basis functions and corresponding coefficients; for the data Y(t) in the transformation basis domain, x basis e_1(t) ⁇ e_x(t) can be used to approximate it, Make the data Y(t) approximately equal to the sum of x transformation bases multiplied by the corresponding transformation coefficients.
  • the transformation base includes but is not limited to: spherical harmonic function base, spherical wavelet base, eigenvector, etc., which is not limited in this application.
  • the second rearrangement module may be used to rearrange data.
  • Figure 8b is only an example of the data form conversion module of the embodiment of the present application.
  • the data form conversion module of the embodiment of the present application may have fewer modules than Figure 8b.
  • the data form conversion module only includes domains. Conversion module; for another example, the data form conversion module only includes a quantization module and a domain conversion module; for another example, the data form conversion module only includes a domain conversion module and a second rearrangement module, and the embodiment of the present application does not limit this.
  • the data format conversion module in the embodiment of the present application may have more modules than in Figure 8b, and the embodiment of the present application does not limit this.
  • the quantization module, the domain conversion module and the second rearrangement module in Figure 8b can be independent modules, or any two or more of them can be integrated into a whole.
  • the embodiment of the present application is suitable for This is not a limitation.
  • the quantization module, the domain conversion module and the second rearrangement module are logical modules, and the data form conversion module can also be divided into other modules or these modules adopt other names, and the embodiments of this application are not limited to this.
  • Figure 9a is a schematic diagram of an exemplary decoding framework.
  • a decoding framework corresponding to the encoding framework in Figure 8a is described.
  • the decoder may include: a data form conversion module, a first rearrangement module and a decoding module.
  • the data form conversion module can be used to convert part of the data decoded from the code stream into data forms to obtain probe data.
  • the first rearrangement module can be used to rearrange and distribute another part of data decoded from the code stream, To get the property data of the probe.
  • the attribute data of the probe may include attribute data used for data form conversion (hereinafter referred to as first attribute data), and the above-mentioned attribute data used in the rendering process (hereinafter referred to as second attribute data).
  • the decoding module is used to decode the code stream.
  • the data form conversion process of the data form conversion module in the decoder is the inverse process of the data form conversion process of the data form conversion module in the encoder; and the re-arrangement module of the decoder.
  • the arrangement process is the reverse process of the rearrangement process of the first rearrangement module in the encoder.
  • the steps performed by the data format conversion module and the first rearrangement module belong to the steps in the decoding process of the decoder.
  • Figure 9a is only an example of the decoder of the embodiment of the present application.
  • the decoder of the embodiment of the present application may have fewer modules than Figure 9a.
  • the decoder includes a data form conversion module and a decoding module.
  • the embodiments of the present application do not limit this.
  • the decoder in the embodiment of the present application may have more modules than shown in Figure 9a, and the embodiment of the present application does not limit this.
  • the data form conversion module, the first rearrangement module and the decoding module in Figure 9a can be independent modules, or any two or more modules thereof can be integrated into one body. There are no restrictions on this.
  • the data format conversion module, the first rearrangement module and the decoding module are logical modules, and the decoder can also be divided into other modules or these modules adopt other names, and the embodiments of this application are not limited to this.
  • the decoder only includes a decoding module, a data format conversion module and a first rearrangement module, and may be independent of the decoder, which is not limited in the embodiments of the present application.
  • This embodiment of the present application takes the decoder in Figure 9a as an example for illustrative description.
  • Figure 9b is a schematic structural diagram of an exemplary data format conversion module.
  • the data form conversion module may include: an inverse quantization module, a domain conversion module and a second rearrangement module.
  • an inverse quantization module can be used for inverse quantization. It should be understood that the inverse quantization process of the inverse quantization module in the decoder is the inverse process of the quantization process of the quantization module in the encoder.
  • a domain conversion module can be used for domain conversion. It should be understood that the domain conversion process of the domain conversion module in the decoder is the reverse process of the domain conversion process of the domain conversion module in the encoder.
  • the second rearrangement module may be used to rearrange data. It should be understood that the rearrangement process of the second rearrangement module in the decoder is the reverse process of the rearrangement process of the second rearrangement module in the encoder.
  • Figure 9b is only an example of the data form conversion module in this embodiment of the present application, and the data form conversion module in this embodiment of the present application may have fewer modules than Figure 9b.
  • the data form conversion module only includes an inverse quantization module and a domain conversion module, or the data form conversion module only includes a domain conversion module and a second rearrangement module. This is not limited in the embodiments of the present application.
  • the data format conversion module in the embodiment of the present application may have more modules than in Figure 9b, and the embodiment of the present application does not limit this.
  • the inverse quantization module, the domain conversion module and the second rearrangement module in Figure 9b can be independent modules, or any two or more of them can be integrated into a whole. According to the embodiment of the present application There are no restrictions on this.
  • the inverse quantization module, the domain conversion module and the second rearrangement module are logical modules, and the data form conversion module can also be divided into other modules or these modules adopt other names, and the embodiments of the present application do not limit this.
  • Figures 10 and 11 are flow charts of the encoding method provided by embodiments of the present application.
  • This encoding method can be performed by the decoder described above.
  • the coding method is described as a series of steps or operations. It should be understood that coding Methods may be performed in various orders and/or occur simultaneously and are not limited to the order of execution shown in Figure 10.
  • the encoding method may include:
  • the above-mentioned target normalization combination is a normalization combination that minimizes the rendering loss corresponding to the above-mentioned probe data group among multiple normalization combinations.
  • the above-mentioned target normalization combination includes a target normalization method and a target normalization method. parameter.
  • the rendering loss corresponding to the probe data group can be the error between the rendering effect corresponding to the probe data group and the rendering effect corresponding to the encoded and decoded probe data group.
  • the above rendering loss can be measured by PSNR, or MSE or other parameters, which are not limited in the embodiments of the present application.
  • the probe data set may include probe data for a single row of probes in one or more frames, probe data for a single probe in one or more frames, probe data for a single channel probe in one or more frames. data or probe data for all probes in one or more frames.
  • the probe data corresponds to one or more probes in the three-dimensional scene and is used to determine the coloring effect of objects in the three-dimensional scene during the rendering process, and may include attribute data and surrounding environment data.
  • the surrounding environment data in the probe data refers to the attribute data in different directions of each probe, such as lighting data, color, visibility data, material, normal direction, texture coordinates and other information.
  • the attribute data in the probe data can include: the type of the probe, whether the probe is enabled, the position of the probe, the offset of the probe relative to the initial position, the parameters used in the encoding process of the surrounding environment data, etc., etc. One thing is enough.
  • the computing center server can use multiple probes placed in the cloud game scene to detect the surrounding environment to generate probe data corresponding to the game scene from the target perspective;
  • the probe data group consisting of the probe data is then sent to the edge server.
  • a target normalized combination of probe data sets is determined by the edge server.
  • the computing center server after the computing center server receives the instruction to add furniture sent by the client, it can use multiple probes placed in the indoor decoration scene to detect the surrounding environment to generate the corresponding living room scene after adding the target furniture. Probe data; then send the probe data group consisting of the probe data to the edge server. A target normalized combination of probe data sets is determined by the edge server.
  • the rendering loss corresponding to the probe data group for each of the multiple normalized combinations may be first determined. Then, the normalization combination that minimizes the rendering loss corresponding to the probe data group among the multiple normalization combinations is determined as the target normalization combination.
  • a target operation can be performed on the probe data group based on each of the above normalized combinations to obtain the rendering result of each of the above normalized combinations on the above probe data group. Then, based on the rendering result obtained by rendering the above-mentioned probe data group through the above-mentioned target operation and the rendering result obtained by rendering the above-mentioned probe data group without the above-mentioned target operation, it is determined that each of the above-mentioned normalized combinations corresponds to the above-mentioned probe data group. Rendering loss.
  • the target operations include normalization, encoding and decoding, and denormalization.
  • the specific encoding and decoding methods mentioned above can be processed by any method that can be thought of by those skilled in the art, and the embodiments of the present application do not specifically limit this.
  • the specific encoding and decoding methods may be encoding and decoding methods such as HEVC, analog encoding and decoding, low-resolution encoding and decoding, and fast encoding and decoding.
  • the above-mentioned multiple normalization combinations may be a normalization combination composed of a min-max normalization method and multiple normalization parameters.
  • M is the maximum normalization parameter
  • m is the minimum normalization parameter
  • the method may further include: determining the normalization parameters in the plurality of normalization combinations according to the reference target normalization parameters, where the reference target normalization parameters are the same as those of the probes.
  • Target normalization parameter for the probe data set associated with the data set may be determining the normalization parameters in the plurality of normalization combinations according to the reference target normalization parameters, where the reference target normalization parameters are the same as those of the probes.
  • multiple values may be selected within the range of 1/(1+ ⁇ ) times to 1+ ⁇ times the reference target normalization parameter as the normalization parameters in the multiple normalization combinations.
  • ⁇ can range from 0.01 to 0.05.
  • the target normalization parameters (such as M and m) of the probe data group of the current frame can be 1/(1+ ⁇ ) times to 1 of the target normalization parameters of the probe data group of the previous frame. Within the range of + ⁇ times.
  • the target normalization parameter M of the data ranges from 0.99 to 1.01.
  • multiple normalization parameters in the above multiple normalization combinations may be 1.
  • the computing center server can use multiple probes placed in the cloud game scene to detect the surrounding environment to generate probe data corresponding to the game scene from the target perspective;
  • the probe data group consisting of the probe data is then sent to the edge server.
  • the edge server determines a target normalized combination of the probe data set, and then normalizes the probe data set according to the target normalized combination to obtain a normalized probe data set.
  • the computing center server can use multiple probes placed in the indoor decoration scene to detect the surrounding environment to generate the corresponding living room scene after adding the target furniture.
  • Probe data then send the probe data group consisting of the probe data to the edge server.
  • the edge server determines a target normalized combination of the probe data set, and then normalizes the probe data set according to the target normalized combination to obtain a normalized probe data set.
  • the above-mentioned probe data set is normalized according to the above-mentioned target normalization combination to obtain a normalized probe data set, which can be processed by any method that can be thought of by those skilled in the art.
  • the target normalization method in the above target normalization combination is preset maximum value normalization
  • the target normalization method in the above target normalization combination is max-min normalization
  • the target normalization method in the above target normalization combination is Z-Score normalization
  • the edge server can compile the data set into the code stream of the game scene.
  • the edge server can, after obtaining the probe data group corresponding to the normalized living room scene, compile the data group into the code stream of the living room scene.
  • the above target normalized combination can also be encoded into the above code stream.
  • the change amount of the normalization parameter of the probe data set can also be determined based on the target normalization parameter of the probe data set and the reference target normalization parameter;
  • the variation is encoded into the above code stream.
  • the above-mentioned reference target normalization parameter is a target normalization parameter of the probe data group related to the above-mentioned probe data group.
  • the target normalized combination is encoded into the code stream.
  • the above method may further include: sending normalization information, where the above normalization information is used to indicate the target normalization combination.
  • the change amount of the normalization parameter of the probe data set can also be determined based on the target normalization parameter of the probe data set and the reference target normalization parameter, and the normalization parameter can be Variations are encoded into the code stream.
  • Intra-frame coding is a coding method that only uses the current frame information when encoding the current frame.
  • the intra-frame coding of HEVC can be used to complete the intra-frame coding of the probe data group; inter-frame coding is used when encoding the current frame.
  • the inter-frame coding of HEVC can be used to complete the inter-frame coding of the probe data group.
  • the change amount of the normalization parameter of the above-mentioned probe data group can also be determined based on the target normalization parameter of the above-mentioned probe data group and the reference target normalization parameter.
  • the above-mentioned reference target normalization parameter The parameter is a target normalization parameter of the probe data group related to the above-mentioned probe data group; the first information is encoded into the above-mentioned code stream, and the above-mentioned first information is used to indicate the target normalization parameter of the above-mentioned probe data group Whether the normalization parameters have changed compared with the above reference target.
  • the first information can be encoded into the code stream.
  • the inter-frame coding method may be other coding methods except the intra-frame coding method.
  • the first information may use different flag bits to indicate whether the target normalization parameter of the probe data set changes compared with the reference target normalization parameter.
  • the above method may further include: in the case where the above first information indicates that the target normalization parameter of the above probe data group changes compared with the above reference target normalization parameter, the above normalization parameter The parameter changes are encoded into the above code stream.
  • the target normalized combination can be encoded into the code stream.
  • the probe data set is a probe data set through inter-frame encoding
  • a marker indicating whether the target normalization parameter has changed is encoded into the code stream, and the target normalization parameter of the probe data set is compared with the above reference.
  • the target normalization parameter changes, the above-mentioned change amount of the normalization parameter is encoded into the above-mentioned code stream.
  • the information includes the identification of the probe data set and the normalized parameter variation of the probe data set.
  • the encoding method provided by the embodiment of the present application does not use a certain fixed normalization method and normalization parameters during the normalization process, but selects from multiple normalization methods and normalization parameters. Among the combinations, select the combination of normalization method and normalization parameters that minimizes the rendering loss corresponding to the probe data. Compared with using fixed normalization methods and normalization parameters, normalization using a combination of normalization methods and normalization parameters that minimizes the rendering loss corresponding to probe data can reduce the effects of compressing probe data. rendering loss.
  • Figures 15 and 16 are flow charts of the decoding method provided by embodiments of the present application.
  • This decoding method can be performed by the above-mentioned decoder.
  • the decoding method is described as a series of steps or operations. It should be understood that the decoding method can be executed in various orders and/or occur simultaneously, and is not limited to the execution order shown in Figures 15 and 16.
  • the decoding method may include:
  • the client after obtaining the code stream of the game scene, the client can decode the code stream to obtain a normalized probe data set of the game scene.
  • the client can decode the code stream to obtain a normalized probe data set corresponding to the living room scene.
  • S1502. Denormalize the above-mentioned normalized probe data set according to the target normalization combination of the probe data set to obtain a second probe data set.
  • the above-mentioned target normalization combination is a normalization combination that minimizes the rendering loss corresponding to the above-mentioned first probe data group among multiple normalization combinations.
  • the above-mentioned first probe data group is the above-mentioned normalization before normalization.
  • Probe data set, the above target normalization combination includes target normalization method and target normalization parameters.
  • the client can perform denormalization on the normalized probe data group of the game scene according to the target normalized combination of the probe data group of the game scene to obtain the probe data of the game scene. Needle data group.
  • the client can denormalize the probe data group corresponding to the normalized living room scene according to the target normalized combination of the probe data group corresponding to the living room scene to obtain the living room.
  • the probe data group corresponding to the scene can denormalize the probe data group corresponding to the normalized living room scene according to the target normalized combination of the probe data group corresponding to the living room scene to obtain the living room.
  • the probe data group corresponding to the scene can denormalize the probe data group corresponding to the normalized living room scene according to the target normalized combination of the probe data group corresponding to the living room scene to obtain the living room.
  • the probe data group corresponding to the scene can denormalize the probe data group corresponding to the normalized living room scene according to the target normalized combination of the probe data group corresponding to the living room scene to obtain the living room.
  • the above target normalized combination can also be obtained.
  • the above target normalized combination can be obtained by obtaining normalized information.
  • the above normalized information is used to indicate the target normalized combination
  • the above target normalized combination can be obtained by decoding the above code stream.
  • the target normalized combination can be obtained by decoding the code stream.
  • the code stream may be decoded first to obtain the normalized parameter variation of the first probe data group. Then the above target normalization combination is determined based on the above normalization parameter variation and the reference normalization combination.
  • the reference normalization combination is a target normalization combination of the probe data set related to the above-mentioned first probe data set.
  • the normalized probe data set is a probe data set encoded by inter-frame coding
  • it can be determined based on the target normalization parameter of the first probe data set and the reference target normalization parameter.
  • the normalized parameter variation of the above-mentioned first probe data set is a probe data set encoded by inter-frame coding
  • determining whether a probe data group is related to the current probe data group can be measured through a variety of measurement methods.
  • the embodiments of the present application are not limited to this, which include but are not limited to, calculating two probe data groups. skin between Pearson correlation coefficient. If the Pearson correlation coefficient is greater than the second preset threshold, it is considered that one of the two probe data sets is related to the other; in addition, the relationship between the two probe data sets can also be calculated. PSNR, if the PSNR is greater than the preset threshold, one of the two probe data sets is considered to be related to the other set.
  • the code stream may be decoded first to obtain first information, where the first information indicates that the target normalization parameter of the first probe data group is smaller than the reference target normalization parameter. If there is no change, determine the above target normalization combination based on the reference normalization combination.
  • the above-mentioned first information is used to indicate whether the target normalization parameter of the above-mentioned first probe data group has changed compared with the above-mentioned reference target normalization parameter, and the above-mentioned reference normalization combination is related to the above-mentioned first probe data group.
  • Target normalized combination of probe data sets are used to indicate whether the target normalization parameter of the above-mentioned first probe data group has changed compared with the above-mentioned reference target normalization parameter.
  • the code stream can be decoded first to obtain the first information, and the first information indicates the first probe
  • the reference normalization combination is determined to be the above-mentioned target normalization combination.
  • the code stream may be decoded first to obtain first information, where the first information indicates that the target normalization parameter of the first probe data group is smaller than the reference target normalization parameter. If a change occurs, the code stream is decoded to obtain the normalized parameter change amount of the first probe data group and the target normalized combination is determined based on the normalized parameter change amount and the reference normalized combination.
  • the code stream can be decoded first to obtain the first information, and the first information indicates the first probe
  • the above-mentioned code stream is decoded to obtain the change amount of the normalization parameter of the above-mentioned first probe data group and based on the above-mentioned normalization parameter
  • the variation amount and the above-mentioned reference normalization combination determine the above-mentioned target normalization combination.
  • the specific method of rendering according to the second probe data group can be processed by any method that those skilled in the art can think of, and this is not specifically limited in the embodiments of the present application.
  • the client can render the game scene according to the probe data group of the game scene.
  • the client can render the living room scene according to the probe data group corresponding to the living room scene.
  • the encoding device used to perform the above decoding method is introduced below.
  • the encoding device may include: a data form conversion module and an encoding module.
  • the data form conversion module is used to determine the target normalized combination of the probe data set.
  • the above-mentioned target normalization combination is a normalization combination that minimizes the rendering loss corresponding to the above-mentioned probe data group among multiple normalization combinations.
  • the above-mentioned target normalization combination includes a target normalization method and a target normalization method. parameter.
  • the data form conversion module can be used to perform S1001 in the above encoding method.
  • the data form conversion module is also used to normalize the probe data set according to the target normalization combination to obtain a normalized probe data set.
  • the data form conversion module may be used to perform S1002 in the above encoding method.
  • the encoding module is used to encode the above-mentioned normalized probe data group into the code stream.
  • the encoding module may be used to perform S1003 in the above encoding method.
  • the above-mentioned data form conversion module is specifically used to: determine the rendering loss corresponding to the above-mentioned probe data group for each of the above-mentioned multiple normalization combinations; Among the normalization combinations, the normalization combination that minimizes the rendering loss corresponding to the above-mentioned probe data group is determined as the above-mentioned target normalization combination.
  • the above-mentioned data form conversion module is specifically configured to: perform a target operation on the above-mentioned probe data group according to each of the above-mentioned normalized combinations to obtain the above-mentioned value of each of the above-mentioned normalized combinations for the above-mentioned probe data group.
  • the rendering result of The rendering result determines the rendering loss corresponding to each of the above normalized combinations for the above probe data set.
  • the above-mentioned encoding module is also used to: encode the above-mentioned target normalized combination into the above-mentioned code stream.
  • the above-mentioned data form conversion module is also used to: determine the change amount of the normalization parameter of the above-mentioned probe data group according to the target normalization parameter of the above-mentioned probe data group and the reference target normalization parameter.
  • the above-mentioned reference target normalization parameter is the target normalization parameter of the probe data group related to the above-mentioned probe data group;
  • the above-mentioned encoding module is also used to encode the above-mentioned normalized parameter variation into the above-mentioned code stream.
  • the encoding module is also used to encode first information into the code stream, and the first information is used to indicate that the target normalization parameter of the probe data group is normalized better than the reference target. Whether the normalization parameters have changed.
  • the encoding module is further configured to: when the first information indicates that the target normalization parameter of the probe data group changes from the reference target normalization parameter, convert the normalization parameter to The normalized parameter variation is encoded into the above code stream.
  • the encoding module is further configured to encode index information into the code stream, where the index information includes an identification of the probe data group and a normalized parameter variation of the probe data group.
  • the above-mentioned data form conversion module is also used to: determine the normalization parameters in the above-mentioned multiple normalization combinations according to the above-mentioned reference target normalization parameters, the above-mentioned reference target normalization parameters are and The target normalization parameter of the probe data set related to the above probe data set.
  • the probe data set includes surrounding environment data of the probe, and the surrounding environment data includes at least one of illumination data, color, visibility data, material, normal direction, or texture coordinates.
  • the decoding device may include: a data form conversion module and a data form conversion module.
  • Decoding module used to decode the code stream to obtain the normalized probe data set.
  • the decoding module may be used to perform S1501 in the above decoding method.
  • a data form conversion module configured to denormalize the normalized probe data set according to the target normalized combination of the first probe data set to obtain a second probe data set, the target normalized The combination is a normalized combination with the smallest rendering loss corresponding to the first probe data group among multiple normalized combinations, and the first probe data group is the normalized probe before normalization.
  • a data set, the target normalization combination includes a target normalization method and a target normalization parameter.
  • the data form conversion module may be used to perform S1502 in the above decoding method.
  • the data form conversion module is also used for rendering based on the above-mentioned second probe data group.
  • the data form conversion module may be used to perform S1503 in the above decoding method.
  • the above decoding module is also used to obtain the above target normalized combination.
  • the above-mentioned decoding module is specifically configured to: decode the above-mentioned code stream to obtain the above-mentioned target normalized combination.
  • the above-mentioned decoding module is specifically configured to: decode the above-mentioned code stream to obtain the normalized parameter variation of the above-mentioned first probe data group; according to the above-mentioned normalized parameter variation and the reference normalization The combination determines the target normalized combination, and the reference normalized combination is the target normalized combination of the probe data set related to the first probe data set.
  • the above-mentioned decoding module is specifically configured to: decode the above-mentioned code stream to obtain first information, the above-mentioned first information is used to indicate that the target normalization parameter of the above-mentioned first probe data group is better than the above-mentioned reference target.
  • the above-mentioned reference target normalization parameter is the target normalization parameter of the probe data group related to the above-mentioned first probe data group; when the above-mentioned first information indicates the above-mentioned first probe data group
  • the above-mentioned target normalization combination is determined based on the reference normalization combination, and the above-mentioned reference normalization combination is the same as the above-mentioned first probe data set.
  • Target normalization combination of the relevant probe data group in the case where the first information indicates that the target normalization parameter of the first probe data group changes compared with the reference target normalization parameter, decoding
  • the code stream is used to obtain second information.
  • the second information is used to indicate the normalized parameter variation of the first probe data group and is normalized according to the normalized parameter variation and the reference normalization.
  • the combination determines the target normalization combination.
  • An embodiment of the present application also provides an encoding device, which includes: at least one processor.
  • the at least one processor executes program codes or instructions, the above related method steps are implemented to implement the encoding method in the above embodiment.
  • the device may further include at least one memory for storing the program code or instructions.
  • An embodiment of the present application also provides a decoding device, which includes: at least one processor.
  • a decoding device which includes: at least one processor.
  • the at least one processor executes program codes or instructions, the above related method steps are implemented to implement the decoding method in the above embodiment.
  • the device may further include at least one memory for storing the program code or instructions.
  • Embodiments of the present application also provide a computer storage medium.
  • Computer instructions are stored in the computer storage medium.
  • the encoding device executes the above related method steps to implement the encoding and decoding methods in the above embodiments. .
  • An embodiment of the present application also provides a computer program product.
  • the computer program product When the computer program product is run on a computer, it causes the computer to perform the above related steps to implement the encoding and decoding method in the above embodiment.
  • An embodiment of the present application also provides a coding and decoding device.
  • This device may be a chip, an integrated circuit, a component or a module.
  • the device may include a connected processor and a memory for storing instructions, or the device may include at least one processor for retrieving instructions from an external memory.
  • the processor can execute instructions to cause the chip to perform the encoding and decoding methods in the above method embodiments.
  • FIG. 17 shows a schematic structural diagram of a chip 1700.
  • Chip 1700 includes one or more processors 1701 and interface circuits 1702 .
  • the above chip 1700 may also include a bus 1703.
  • the processor 1701 may be an integrated circuit chip with signal processing capabilities. During the implementation process, each step of the above encoding and decoding method can be completed by instructions in the form of hardware integrated logic circuits or software in the processor 1701 .
  • the above-mentioned processor 1701 can be a general-purpose processor, a digital signal processor (digital signal processing, DSP), an integrated circuit (application specific integrated circuit, ASIC), or a field-programmable gate array (field-programmable gate array). , FPGA) or other programmable logic devices, discrete gate or transistor logic devices, discrete hardware components.
  • DSP digital signal processing
  • ASIC application specific integrated circuit
  • FPGA field-programmable gate array
  • a general-purpose processor may be a microprocessor or the processor may be any conventional processor, etc.
  • the interface circuit 1702 can be used to send or receive data, instructions or information.
  • the processor 1701 can use the data, instructions or other information received by the interface circuit 1702 to process, and can send the processed information through the interface circuit 1702.
  • the chip also includes a memory, which may include read-only memory and random access memory, and provides operating instructions and data to the processor.
  • a memory which may include read-only memory and random access memory, and provides operating instructions and data to the processor.
  • Part of the memory may also include non-volatile random access memory (NVRAM).
  • NVRAM non-volatile random access memory
  • the memory stores executable software modules or data structures
  • the processor can perform corresponding operations by calling operating instructions stored in the memory (the operating instructions can be stored in the operating system).
  • the chip can be used in the encoding device or DOP involved in the embodiment of the present application.
  • the interface circuit 1702 may be used to output execution results of the processor 1701.
  • processor 1701 and the interface circuit 1702 can be realized through hardware design, software design, or a combination of software and hardware, which are not limited here.
  • the device, computer storage medium, computer program product or chip provided in this embodiment is used to execute the corresponding method provided above. Therefore, the beneficial effects it can achieve can refer to the corresponding method provided above. The beneficial effects will not be repeated here.
  • the size of the sequence numbers of the above-mentioned processes does not mean the order of execution.
  • the execution order of each process should be determined by its functions and internal logic, and should not be used in this application.
  • the implementation of the examples does not constitute any limitations.
  • the disclosed systems, devices and methods can be implemented in other ways.
  • the device embodiments described above are only illustrative.
  • the division of the above units is only a logical function division. In actual implementation, there may be other division methods.
  • multiple units or components may be combined or may be Integrated into another system, or some features can be ignored, or not implemented.
  • the coupling or direct coupling or communication connection between each other shown or discussed may be through some interfaces, indirect coupling or communication connection of devices or units, which may be in electrical, mechanical or other forms.
  • the units described above as separate components may or may not be physically separated.
  • the components shown as units may or may not be physical units, that is, they may be located in one place, or they may be distributed to multiple networks. on the unit. Some or all of the units can be selected according to actual needs to achieve the purpose of the solution of this embodiment.
  • each functional unit in each embodiment of the present application can be integrated into one processing unit, or each unit can exist physically alone, or two or more units can be integrated into one unit.
  • the technical solutions of the embodiments of the present application are essentially or the part that contributes to the existing technology or the part of the technical solution can be embodied in the form of a software product, and the computer software product is stored in a storage medium , including several instructions to cause a computer device (which may be a personal computer, a server, or a network device, etc.) to execute all or part of the steps of the above methods in various embodiments of the embodiments of this application.
  • the aforementioned storage media include: U disk, mobile hard disk, Read Only Memory (ROM), Random Access Memory (RAM), magnetic disk or optical disk and other media that can store program code.

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Abstract

本申请实施例公开了编解码方法和装置，涉及媒体技术领域，能够减少压缩探针数据造成的渲染损失。其中编码方法包括：首先确定探针数据组的目标归一化组合，然后根据所述目标归一化组合对所述探针数据组进行归一化以得到归一化探针数据组，之后将所述归一化探针数据组编入码流。其中，所述目标归一化组合为多个归一化组合中使所述探针数据组对应的渲染损失最小的归一化组合，所述目标归一化组合包括目标归一化方法和目标归一化参数。

Description

编解码方法和装置
本申请要求于2022年03月15日提交中国专利局、申请号为202210254653.7、申请名称为“编解码方法和装置”的中国专利申请的优先权，其全部内容通过引用结合在本申请中。
技术领域
本申请实施例涉及媒体技术领域，尤其涉及编解码方法和装置。
背景技术
随着软硬件技术的发展，人们对于计算机渲染***产生的画面的质量追求越来越高，从以往的仅有直接光照逐渐过渡到有更多和更真实的光照效果。探针是渲染***中模拟光照效果的常用手段之一。在实际应用中单个场景的探针数量时常达到上千上万，对于大规模场景甚至可达到几十万。由于探针的数据可以随时间的变化而改变，存储、访问和传输探针数据会产生大量的开销。为此需要通过压缩探针数据以降低探针数据的存储、访问和传输的开销。
然而，压缩探针数据会影响渲染效果造成渲染损失。如何减少压缩探针数据造成的渲染损失是本领域技术人员急需解决的问题之一。
发明内容
本申请实施例提供了编解码方法和装置，能够减少压缩探针数据造成的渲染损失。为达到上述目的，本申请实施例采用如下技术方案：
第一方面，本申请实施例提供了一种编码方法，该方法包括：首先确定探针数据组的目标归一化组合，然后根据所述目标归一化组合对所述探针数据组进行归一化以得到归一化探针数据组，之后将所述归一化探针数据组编入码流。其中，所述目标归一化组合为多个归一化组合中使所述探针数据组对应的渲染损失最小的归一化组合，所述目标归一化组合包括目标归一化方法和目标归一化参数。
其中，探针数据与三维场景中的一个或多个探针对应，用于在渲染过程中确定所述三维场景中对象的着色效果。探针数据组可以包括一帧或多帧中的单行探针的探针数据、一帧或多帧中的单个探针的探针数据、一帧或多帧中的单个通道探针的探针数据或一帧或多帧中的所有探针的探针数据。
可以看出，本申请实施例提供的编码方法在归一化过程中，不使用某种固定的归一化方法和归一化参数，而是从多个归一化方法和归一化参数的组合中，选取使探针数据对应的渲染损失最小的归一化方法和归一化参数的组合。相较于使用固定的归一化方法和归一化参数，使用使探针数据对应的渲染损失最小的归一化方法和归一化参数的组合进行归一化，能够减少压缩探针数据造成的渲染损失。
可选地，探针数据(probe data)组对应的渲染损失(rendering loss)，可以是探针数据 组对应的渲染效果与探针数据组经过编解码后对应的渲染效果之间的误差。比如，上述渲染损失可以用峰值信噪比(peak signal to noise ratio，PSNR)进行度量，也可以用均方根误差(mean squared error，MSE)或其他参数进行度量，本申请实施例对此不作限定。
在一种可能的实现方式中，所述确定探针数据组的目标归一化组合，可以包括：确定所述多个归一化组合中每个归一化组合对于所述探针数据组对应的渲染损失；将所述多个归一化组合中使所述探针数据组对应的渲染损失最小的归一化组合确定为所述目标归一化组合。
可以理解的是，通过确定多个归一化组合中每个归一化组合对于探针数据组对应的渲染损失，然后将多个归一化组合中使探针数据组对应的渲染损失最小的归一化组合确定为目标归一化组合，之后使用使探针数据对应的渲染损失最小的归一化方法和归一化参数的组合(即目标归一化组合)进行归一化，能够减少压缩(归一化)探针数据造成的渲染损失。
在一种可能的实现方式中，上述确定所述多个归一化组合中每个归一化组合对于所述探针数据组对应的渲染损失，可以包括：根据所述每个归一化组合对所述探针数据组进行目标操作以得到所述每个归一化组合对于所述探针数据组的渲染结果；根据所述探针数据组经所述目标操作进行渲染得到的渲染结果和所述探针数据组未经所述目标操作进行渲染得到的渲染结果确定所述每个归一化组合对于所述探针数据组对应的渲染损失。其中，目标操作包括归一化、编解码和反归一化。
其中，上述编解码的具体方法可以采用本领域技术人员能够想到的任何一种方法进行处理，本申请实施例对此不作具体限定。例如，编解码的具体方法可以为高效率视频编码(high efficiency video coding，HEVC)、模拟编解码、低分辨率编解码、快速编解码等编解码方法。
可以理解的是，根据每个归一化组合对所述探针数据组进行目标操作可以得到每个归一化组合对应的渲染结果，然后通过对比探针数据组经目标操作得到的渲染结果和探针数据未经目标操作得到的渲染结果可以得到每个归一化组合对于探针数据组对应的渲染损失。之后使用使探针数据对应的渲染损失最小的归一化组合进行归一化，能够减少压缩(归一化)探针数据造成的渲染损失。
在一种可能的实现方式中，上述方法还可以包括：将所述目标归一化组合编入所述码流。
可以理解的是，将探针数据组的目标归一化组合编入码流后，解码端可以通过解码该码流快速获取探针数据组的目标归一化组合，然后通过该目标归一化组合对归一化探针数据组进行反归一化得到探针数据组。
在一种可能的实现方式中，上述将所述目标归一化组合编入码流，可以包括：在所述探针数据组为通过帧内编码的探针数据组的情况下，将所述目标归一化组合编入所述码流。
帧内编码为编码当前帧时只使用了当前帧信息的编码方式，示例性的，可以使用HE VC的帧内编码来完成探针数据组的帧内编码；帧间编码为编码当前帧时使用了非当前帧信息的编码方式，示例性的，可以使用HEVC的帧间编码来完成探针数据组的帧间编码。
在一种可能的实现方式中，上述方法还可以包括：根据所述探针数据组的目标归一化参数和参考目标归一化参数确定所述探针数据组的归一化参数变化量；将所述归一化参数 变化量编入所述码流。其中，所述参考目标归一化参数为与所述探针数据组相关的探针数据组的目标归一化参数。
其中，判断一个探针数据组是否与当前探针数据组是相关的，可以通过多种度量方式进行度量，本申请实施例对此不作限定，其包括但不限于，计算两个探针数据组之间的皮尔逊相关系数，如果皮尔逊相关系数大于第二预设阈值，则认为两组探针数据组中的一组与另一组是相关的；此外，也可以计算两个探针数据组之间的PSNR，如果PSNR大于预设阈值，则认为两组探针数据组中的一组与另一组是相关的。
可以理解的是，相较于将探针数据组的目标归一化组合编入码流，将探针数据组的归一化参数变化量编入码流可以降低开销，且在将探针数据组的归一化参数变化量编入码流后，解码端可以通过解码该码流快速获取探针数据组的归一化参数变化量，然后通过该归一化参数变化量确定探针数据组的目标归一化组合，之后通过该目标归一化组合对归一化探针数据组进行反归一化得到探针数据组。
在一种可能的实现方式中，上述将所述归一化参数变化量编入所述码流，可以包括：在所述探针数据组为通过帧间编码的探针数据组的情况下，将所述归一化参数变化量编入所述码流。
在一种可能的实现方式中，上述方法还可以包括：根据所述探针数据组的目标归一化参数和参考目标归一化参数确定所述探针数据组的归一化参数变化量，所述参考目标归一化参数为与所述探针数据组相关的探针数据组的目标归一化参数；将第一信息编入所述码流中，所述第一信息用于指示所述探针数据组的目标归一化参数较所述参考目标归一化参数是否发生变化。
可选地，当前帧的探针数据组的参考目标归一化参数可以为当前帧的上一帧的探针数据组的目标归一化参数。
可选地，第一信息可以用不同的标记位指示所述探针数据组的目标归一化参数较所述参考目标归一化参数是否发生变化。
在一种可能的实现方式中，上述方法还可以包括：在所述第一信息指示所述探针数据组的目标归一化参数较所述参考目标归一化参数发生变化的情况下，将所述归一化参数变化量编入所述码流。
可以理解的是，在探针数据组的目标归一化参数较所述参考目标归一化参数发生变化的情况下，相较于将探针数据组的目标归一化组合编入码流，将探针数据组的归一化参数变化量编入码流可以降低开销，且在将探针数据组的归一化参数变化量编入码流后，解码端可以通过解码该码流快速获取探针数据组的归一化参数变化量，然后通过该归一化参数变化量确定探针数据组的目标归一化组合，之后通过该目标归一化组合对归一化探针数据组进行反归一化得到探针数据组。
在一种可能的实现方式中，上述方法还可以包括：将索引信息编入所述码流，所述索引信息包括探针数据组的标识和所述探针数据组的归一化参数变化量。
在一种可能的实现方式中，上述方法还可以包括：根据所述参考目标归一化参数确定所述多个归一化组合中的归一化参数，所述参考目标归一化参数为与所述探针数据组相关的探针数据组的目标归一化参数。
可选地，探针数据组的目标归一化参数可以在参考目标归一化参数的目标归一化参数 的1/(1+∈)倍至1+∈倍的范围以内。其中，∈的范围可以为0.01～0.05。
可选地，上述多个归一化组合可以为由最小最大归一化方法和多个归一化参数组成的归一化组合。
在一种可能的实现方式中，归一化参数可以包括最大归一化参数和最小归一化参数，归一化公式可以满足：
M为最大归一化参数，m为最小归一化参数。
可选地，当前帧的探针数据组的目标归一化参数(如M和m)可以在上一帧的探针数据组的目标归一化参数的1/(1+∈)倍至1+∈倍的范围以内。其中，∈的范围可以为0.01～0.05。
示例性地，假设当前帧的上一帧的探针数据组的目标归一化参数M为1，∈为0.01，则当前帧的探针数据组的目标归一化参数M的取值范围的下限为1/(1+0.01)*1≈0.99，当前帧的探针数据的目标归一化参数M的取值范围的上限为(1+0.01)*1＝1.01，即当前帧的探针数据的目标归一化参数M的取值范围为0.99～1.01。
可选地，目标归一化方法也可以为其他归一化方法。例如，预设最大值归一化方法或标准分数(Z-Score)归一化方法。
可选地，上述探针数据包括探针的周遭环境数据，所述周遭环境数据包括光照数据、颜色、可见性数据(包括距离数据、距离数据的方差和距离数据的平方等数据)、材质、法向或纹理坐标中的至少一项。
需要说明的是，探针数据包括探针的周遭环境数据和探针的属性数据。由于探针的属性数据占用存储空间通常远远少于周遭环境数据，因此本申请实施例提供的方法可以仅对探针的周遭环境数据进行处理。
第二方面，本申请实施例还提供了一种解码方法，该方法包括：先解码码流以得到归一化探针数据组。然后根据第一探针数据组的目标归一化组合对所述归一化探针数据组进行反归一化以得到第二探针数据组。之后根据所述第二探针数据组进行渲染。其中，所述目标归一化组合为多个归一化组合中对于所述第一探针数据组对应的渲染损失最小的归一化组合，所述第一探针数据组为归一化前的所述归一化探针数据组，所述目标归一化组合包括目标归一化方法和目标归一化参数。
本申请实施例提供的解码方法在反归一化过程中，可以通过解码码流得到归一化后的探针数据。然后使用使探针数据对应的渲染损失最小的归一化方法和归一化参数的组合进行反归一化得到探针数据，相较于使用固定的归一化方法和归一化参数进行反归一化，得到的探针数据，使用使探针数据对应的渲染损失最小的归一化组合得到探针数据，在渲染时带来的渲染损失较小，从而能够减少压缩探针数据造成的渲染损失。
可选地，探针数据(probe data)组对应的渲染损失(rendering loss)，可以是探针数据组对应的渲染效果与探针数据组经过编解码后对应的渲染效果之间的误差。比如，上述渲染损失可以用峰值信噪比(peak signal to noise ratio，PSNR)进行度量，也可以用均方根误差(mean squared error，MSE)或其他参数进行度量，本申请实施例对此不作限定。
在一种可能的实现方式中，上述方法还可以包括：获取所述目标归一化组合。
在一种可能的实现方式中，上述获取所述目标归一化组合可以包括：获取目标信息， 所述信息包括所述目标归一化组合。
在另一种可能的实现方式中，上述获取所述目标归一化组合可以包括：解码所述码流以得到所述目标归一化组合。
可以看出，本申请实施例提供的解码方法可以通过解码码流得到归一化后的探针数据和使探针数据对应的渲染损失最小的归一化方法和归一化参数的组合。然后使用该归一化组合进行反归一化得到探针数据，相较于使用固定的归一化方法和归一化参数进行反归一化，得到的探针数据，使用使探针数据对应的渲染损失最小的归一化组合得到探针数据，在渲染时带来的渲染损失较小，从而能够减少压缩探针数据造成的渲染损失。
在一种可能的实现方式中，上述获取所述目标归一化组合，可以包括：解码所述码流以得到所述第一探针数据组的归一化参数变化量；根据所述归一化参数变化量和参考归一化组合确定所述目标归一化组合，所述参考归一化组合为与所述第一探针数据组相关的探针数据组的目标归一化组合。
可选地，所述目标归一化组合中的目标归一化方法可以与所述参考归一化组合中的目标归一化方法相同。
可以看出，本申请实施例提供的解码方法可以通过解码码流得到归一化后的探针数据和归一化参数变化量，然后通过该归一化参数变化量和参考归一化组合得到使探针数据对应的渲染损失最小的归一化方法和归一化参数的组合。然后使用该归一化组合进行反归一化得到探针数据，相较于使用固定的归一化方法和归一化参数进行反归一化，得到的探针数据，使用使探针数据对应的渲染损失最小的归一化组合得到探针数据，在渲染时带来的渲染损失较小，从而能够减少压缩探针数据造成的渲染损失。
在另一种可能的实现方式中，上述获取所述目标归一化组合，可以包括：解码所述码流以得到第一信息，所述第一信息用于指示所述第一探针数据组的目标归一化参数较所述参考目标归一化参数是否发生变化，所述参考目标归一化参数为与所述第一探针数据组相关的探针数据组的目标归一化参数；在所述第一信息指示所述第一探针数据组的目标归一化参数较所述参考目标归一化参数未发生变化的情况下，根据参考归一化组合确定所述目标归一化组合，所述参考归一化组合为与所述第一探针数据组相关的探针数据组的目标归一化组合；在所述第一信息指示所述第一探针数据组的目标归一化参数较所述参考目标归一化参数发生变化的情况下，解码所述码流以得到第二信息，所述第二信息用于指示所述第一探针数据组的归一化参数变化量并根据所述归一化参数变化量和所述参考归一化组合确定所述目标归一化组合。
可选地，所述目标归一化组合可以与所述参考归一化组合相同。例如，在所述第一信息指示所述第一探针数据组的目标归一化参数较所述参考目标归一化参数未发生变化的情况下，所述目标归一化组合可以与所述参考归一化组合相同。
可以看出，本申请实施例提供的解码方法可以通过解码码流得到归一化后的探针数据和目标信息，然后通过目标信息得到使探针数据对应的渲染损失最小的归一化方法和归一化参数的组合。然后使用该归一化组合进行反归一化得到探针数据，相较于使用固定的归一化方法和归一化参数进行反归一化，得到的探针数据，使用使探针数据对应的渲染损失最小的归一化组合得到探针数据，在渲染时带来的渲染损失较小，从而能够减少压缩探针数据造成的渲染损失。
第三方面，本申请实施例还提供了一种编码装置，该装置包括：数据形式转换模块和编码模块；所述数据形式转换模块，用于确定探针数据组的目标归一化组合并根据所述目标归一化组合对所述探针数据组进行归一化以得到归一化探针数据组，所述目标归一化组合为多个归一化组合中使所述探针数据组对应的渲染损失最小的归一化组合，所述目标归一化组合包括目标归一化方法和目标归一化参数；所述编码模块，用于将所述归一化探针数据组编入码流。
在一种可能的实现方式中，所述数据形式转换模块具体用于：确定所述多个归一化组合中每个归一化组合对于所述探针数据组对应的渲染损失；将所述多个归一化组合中使所述探针数据组对应的渲染损失最小的归一化组合确定为所述目标归一化组合。
在一种可能的实现方式中，所述数据形式转换模块具体用于：根据所述每个归一化组合对所述探针数据组进行目标操作以得到所述每个归一化组合对于所述探针数据组的渲染结果，所述目标操作包括归一化、编解码和反归一化；根据所述探针数据组经所述目标操作进行渲染得到的渲染结果和所述探针数据组未经所述目标操作进行渲染得到的渲染结果确定所述每个归一化组合对于所述探针数据组对应的渲染损失。
在一种可能的实现方式中，所述编码模块还用于：将所述目标归一化组合编入所述码流。
在一种可能的实现方式中，所述数据形式转换模块还用于：根据所述探针数据组的目标归一化参数和参考目标归一化参数确定所述探针数据组的归一化参数变化量，所述参考目标归一化参数为与所述探针数据组相关的探针数据组的目标归一化参数；
在一种可能的实现方式中，所述编码模块，还用于将所述归一化参数变化量编入所述码流。
在一种可能的实现方式中，所述编码模块，还用于将第一信息编入所述码流中，所述第一信息用于指示所述探针数据组的目标归一化参数较所述参考目标归一化参数是否发生变化。
在一种可能的实现方式中，所述编码模块还用于：在所述第一信息指示所述探针数据组的目标归一化参数较所述参考目标归一化参数发生变化的情况下，将所述归一化参数变化量编入所述码流。
在一种可能的实现方式中，所述编码模块还用于：将索引信息编入所述码流，所述索引信息包括探针数据组的标识和所述探针数据组的归一化参数变化量。
在一种可能的实现方式中，所述数据形式转换模块还用于：根据所述参考目标归一化参数确定所述多个归一化组合中的归一化参数，所述参考目标归一化参数为与所述探针数据组相关的探针数据组的目标归一化参数。
在一种可能的实现方式中，所述探针数据组包括探针的周遭环境数据，所述周遭环境数据包括光照数据、颜色、可见性数据、材质、法向或纹理坐标中的至少一项。
第四方面，本申请实施例还提供了一种解码装置，该装置包括：解码模块和数据形式转换模块；所述解码模块，用于解码码流以得到归一化探针数据组；所述数据形式转换模块，用于根据第一探针数据组的目标归一化组合对所述归一化探针数据组进行反归一化以得到第二探针数据组并根据所述第二探针数据组进行渲染，所述目标归一化组合为多个归一化组合中对于所述第一探针数据组对应的渲染损失最小的归一化组合，所述第一探针数 据组为归一化前的所述归一化探针数据组，所述目标归一化组合包括目标归一化方法和目标归一化参数。
在一种可能的实现方式中，所述解码模块还用于：获取所述目标归一化组合。
在一种可能的实现方式中，所述解码模块具体用于：解码所述码流以得到所述目标归一化组合。
在一种可能的实现方式中，所述解码模块具体用于：解码所述码流以得到所述第一探针数据组的归一化参数变化量；根据所述归一化参数变化量和参考归一化组合确定所述目标归一化组合，所述参考归一化组合为与所述第一探针数据组相关的探针数据组的目标归一化组合。
在一种可能的实现方式中，所述解码模块具体用于：解码所述码流以得到第一信息，所述第一信息用于指示所述第一探针数据组的目标归一化参数较所述参考目标归一化参数是否发生变化，所述参考目标归一化参数为与所述第一探针数据组相关的探针数据组的目标归一化参数；在所述第一信息指示所述第一探针数据组的目标归一化参数较所述参考目标归一化参数未发生变化的情况下，根据参考归一化组合确定所述目标归一化组合，所述参考归一化组合为与所述第一探针数据组相关的探针数据组的目标归一化组合；在所述第一信息指示所述第一探针数据组的目标归一化参数较所述参考目标归一化参数发生变化的情况下，解码所述码流以得到所述第一探针数据组的归一化参数变化量并根据所述归一化参数变化量和所述参考归一化组合确定所述目标归一化组合。
第五方面，本申请实施例还提供一种编码装置，该装置包括：至少一个处理器，当所述至少一个处理器执行程序代码或指令时，实现上述第一方面或其任意可能的实现方式中所述的方法。
可选地，该装置还可以包括至少一个存储器，该至少一个存储器用于存储该程序代码或指令。
第六方面，本申请实施例还提供一种解码装置，该装置包括：至少一个处理器，当所述至少一个处理器执行程序代码或指令时，实现上述第二方面或其任意可能的实现方式中所述的方法。
可选地，该装置还可以包括至少一个存储器，该至少一个存储器用于存储该程序代码或指令。
第七方面，本申请实施例还提供一种芯片，包括：输入接口、输出接口、至少一个处理器。可选地，该芯片还包括存储器。该至少一个处理器用于执行该存储器中的代码，当该至少一个处理器执行该代码时，该芯片实现上述第一方面或其任意可能的实现方式中所述的方法。
可选地，上述芯片还可以为集成电路。
第八方面，本申请实施例还提供一种计算机可读存储介质，用于存储计算机程序，该计算机程序包括用于实现上述第一方面或其任意可能的实现方式中所述的方法。
第九方面，本申请实施例还提供一种包含指令的计算机程序产品，当其在计算机上运行时，使得计算机实现上述第一方面或其任意可能的实现方式中所述的方法。
本实施例提供的编解码装置、计算机存储介质、计算机程序产品和芯片均用于执行上文所提供的编解码方法，因此，其所能达到的有益效果可参考上文所提供的编解码方法中 的有益效果，此处不再赘述。
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为了更清楚地说明本申请实施例中的技术方案，下面将对实施例描述中所需要使用的附图作简单地介绍，显而易见地，下面描述中的附图仅仅是本申请实施例的一些实施例，对于本领域普通技术人员来讲，在不付出创造性劳动的前提下，还可以根据这些附图获得其他的附图。
图1a为本申请实施例提供的编解码***的一种示例性框图；
图1b为本申请实施例提供的视频编解码***的一种示例性框图；
图2为本申请实施例提供的视频编码器的一种示例性框图；
图3为本申请实施例提供的视频解码器的一种示例性框图；
图4为本申请实施例提供的候选图像块的一种示例性的示意图；
图5为本申请实施例提供的视频译码设备的一种示例性框图；
图6为本申请实施例提供的装置的一种示例性框图；
图7a为本申请实施例提供的一种***框架示意图；
图7b为本申请实施例提供的一种三维场景中探针分布示意图；
图8a为本申请实施例提供的一种编码框架示意图；
图8b为本申请实施例提供的一种数据形式转换模块结构示意图；
图9a为本申请实施例提供的一种解码框架示意图；
图9b为本申请实施例提供的另一种数据形式转换模块结构示意图；
图10为本申请实施例提供的一种编码方法的流程示意图；
图11为本申请实施例提供的另一种编码方法的流程示意图；
图12为本申请实施例提供的一种渲染损失确定方法的流程示意图；
图13为本申请实施例提供的一种编码的流程示意图；
图14为本申请实施例提供的另一种编码的流程示意图；
图15为本申请实施例提供的一种解码方法的流程示意图；
图16为本申请实施例提供的另一种解码方法的流程示意图；
图17为本申请实施例提供的一种芯片的结构示意图。
具体实施方式
下面将结合本申请实施例中的附图，对本申请实施例中的技术方案进行清楚、完整地描述，显然，所描述的实施例仅仅是本申请实施例一部分实施例，而不是全部的实施例。基于本申请实施例中的实施例，本领域普通技术人员在没有做出创造性劳动前提下所获得的所有其他实施例，都属于本申请实施例保护的范围。
本文中术语“和/或”，仅仅是一种描述关联对象的关联关系，表示可以存在三种关系，例如，A和/或B，可以表示：单独存在A，同时存在A和B，单独存在B这三种情况。
本申请实施例的说明书以及附图中的术语“第一”和“第二”等是用于区别不同的对象，或者用于区别对同一对象的不同处理，而不是用于描述对象的特定顺序。
此外，本申请实施例的描述中所提到的术语“包括”和“具有”以及它们的任何变形，意图在于覆盖不排他的包含。例如包含了一系列步骤或单元的过程、方法、***、产品或设备没有限定于已列出的步骤或单元，而是可选的还包括其他没有列出的步骤或单元，或可选的还包括对于这些过程、方法、产品或设备固有的其他步骤或单元。
需要说明的是，本申请实施例的描述中，“示例性地”或者“例如”等词用于表示作例子、例证或说明。本申请实施例中被描述为“示例性地”或者“例如”的任何实施例或设计方案不应被解释为比其他实施例或设计方案更优先或更具优势。确切而言，使用“示例性地”或者“例如”等词旨在以具体方式呈现相关概念。
在本申请实施例的描述中，除非另有说明，“多个”的含义是指两个或两个以上。
首先对本申请实施例涉及的术语进行解释。
反射探针：反射探针是典型的光照探针，它记录了光照数据：以探针为中心，看到的四周的光照情况。其本质是与球面同胚的表面上的数据，可以是球面数据，也可以是立方体表面数据，如图3所示。在使用场景中，反射探针放置在金属球中心，并与金属球面绑定。在渲染时，算法通过计算得到出射的角度，再从探针存储的数据中取出射角度对应的值，即可得到反射之后的应当看到的画面。
动态漫反射全局光照(dynamic diffuse global illumination，DDGI)：使用了多个探针构成的探针体(probe volume)。探针体用于记录光照时，也称为light field probe或i rradiance volume。此外，探针体在precomputed radiance transfer等技术中也有所应用。在DDGI中每个探针与反射探针一样，都会记录各个角度的光照，除此之外，每个探针还会记录可见性数据，即各个角度的物体与这个探针的距离的分布数据，包括每个角度的距离的均值、距离的平方和距离的方差等数据。DDGI数据的存储方式为：单个探针以八面体展开的方式展开成一个正方形图像、多个探针的图像排列成一幅大的图像。为了使用时方便对纹理进行插值，每个探针的正方形图像上下左右会各添加一列冗余的边界数据。
归一化，在探针数据的压缩通过限定数据范围，剔除一些失效数据。在探针数据的压缩、传输和解压缩过程中，是否有归一化、如何进行归一化都会影响渲染的效果。
预设最大值归一化：将数据x变为其中，M为预设的最大值，超出最大值的数据会被截断。预设M可以为1～4之间的实数。在此方案中M即为归一化的参数。
最大最小归一化：将数据x变为归一化到[0,1]之间。归一化参数为max{x}和min{x}。max{x}为数据x中的最大值，min{x}为数据x中的最小值。
Z-Score归一化：将数据x变为其中为x的均值，σ为x的标准差。归一化参数为和σ。
数据编解码包括数据编码和数据解码两部分。数据编码在源侧(或通常称为编码器侧)执行，通常包括处理(例如，压缩)原始数据以减少表示该原始数据所需的数据量(从而更高效存储和/或传输)。数据解码在目的地侧(或通常称为解码器侧)执行，通常包括相对于编码器侧作逆处理，以重建原始数据。本申请实施例涉及的数据的“编解码”应理解为数据的“编码”或“解码”。编码部分和解码部分也合称为编解码器(编码和解码，CODEC)。
在无损数据编码情况下，可以进行重建数据，即重建得到的数据与原始数据具有相同的质量(假设存储或传输期间没有传输损耗或其他数据丢失)。在有损数据编码情况下，通过量化等执行进一步压缩，来减少表示原始数据所需的数据量，而解码器侧无法完全重建原始数据，即重建的原始数据的质量比原始数据的质量低或差。
本申请实施例可以应用于对视频数据以及其他具有压缩/解压缩需求的数据等。以下以视频数据的编码(简称视频编码)为例对本申请实施例进行说明，其他类型的数据(例如图像数据、音频数据、整数型数据以及其他具有压缩/解压缩需求的数据)可以参考以下描述，本申请实施例对此不再赘述。需要说明的是，相对于视频编码，音频数据以及整数型数据等数据的编码过程中无需将数据分割为块，而是可以直接对数据进行编码。
视频编码通常是指处理形成视频或视频序列的图像序列。在视频编码领域，术语“图像(picture)”、“帧(frame)”或“图片(image)”可以用作同义词。
几个视频编码标准属于“有损混合型视频编解码”(即，将像素域中的空间和时间预测与变换域中用于应用量化的2D变换编码结合)。视频序列中的每个图像通常分割成不重叠的块集合，通常在块级上进行编码。换句话说，编码器通常在块(视频块)级处理即编码视频，例如，通过空间(帧内)预测和时间(帧间)预测来产生预测块；从当前块(当前处理/待处理的块)中减去预测块，得到残差块；在变换域中变换残差块并量化残差块，以减少待传输(压缩)的数据量，而解码器侧将相对于编码器的逆处理部分应用于编码或压缩的块，以重建用于表示的当前块。另外，编码器需要重复解码器的处理步骤，使得编码器和解码器生成相同的预测(例如，帧内预测和帧间预测)和/或重建像素，用于处理，即编码后续块。
在以下编解码***10的实施例中，编码器20和解码器30根据图1a至图3进行描述。
图1a为本申请实施例提供的编解码***10的一种示例性框图，例如可以利用本申请实施例技术的视频编解码***10(或简称为编解码***10)。视频编解码***10中的视频编码器20(或简称为编码器20)和视频解码器30(或简称为解码器30)代表可用于根据本申请实施例中描述的各种示例执行各技术的设备等。
如图1a所示，编解码***10包括源设备12，源设备12用于将编码图像等编码图像数据21提供给用于对编码图像数据21进行解码的目的设备14。
源设备12包括编码器20，另外即可选地，可包括图像源16、图像预处理器等预处理器(或预处理单元)18、通信接口(或通信单元)22。
图像源16可包括或可以为任意类型的用于捕获现实世界图像等的图像捕获设备，和/或任意类型的图像生成设备，例如用于生成计算机动画图像的计算机图形处理器或任意类型的用于获取和/或提供现实世界图像、计算机生成图像例如，屏幕内容、虚拟现实(virtual reality，VR)图像和/或其任意组合(例如增强现实(augmented reality，AR)图像)的设备。所述图像源可以为存储上述图像中的任意图像的任意类型的内存或存储器。
为了区分预处理器(或预处理单元)18执行的处理，图像(或图像数据)17也可称为原始图像(或原始图像数据)17。
预处理器18用于接收原始图像数据17，并对原始图像数据17进行预处理，得到预处理图像(或预处理图像数据)19。例如，预处理器18执行的预处理可包括修剪、颜色格式转换(例如从RGB转换为YCbCr)、调色或去噪。可以理解的是，预处理单元18 可以为可选组件。
视频编码器(或编码器)20用于接收预处理图像数据19并提供编码图像数据21(下面将根据图2等进一步描述)。
源设备12中的通信接口22可用于：接收编码图像数据21并通过通信信道13向目的设备14等另一设备或任何其他设备发送编码图像数据21(或其他任意处理后的版本)，以便存储或直接重建。
目的设备14包括解码器30，另外即可选地，可包括通信接口(或通信单元)28、后处理器(或后处理单元)32和显示设备34。
目的设备14中的通信接口28用于直接从源设备12或从存储设备等任意其他源设备接收编码图像数据21(或其他任意处理后的版本)，例如，存储设备为编码图像数据存储设备，并将编码图像数据21提供给解码器30。
通信接口22和通信接口28可用于通过源设备12与目的设备14之间的直连通信链路，例如直接有线或无线连接等，或者通过任意类型的网络，例如有线网络、无线网络或其任意组合、任意类型的私网和公网或其任意类型的组合，发送或接收编码图像数据(或编码数据)21。
例如，通信接口22可用于将编码图像数据21封装为报文等合适的格式，和/或使用任意类型的传输编码或处理来处理所述编码后的图像数据，以便在通信链路或通信网络上进行传输。
通信接口28与通信接口22对应，例如，可用于接收传输数据，并使用任意类型的对应传输解码或处理和/或解封装对传输数据进行处理，得到编码图像数据21。
通信接口22和通信接口28均可配置为如图1a中从源设备12指向目的设备14的对应通信信道13的箭头所指示的单向通信接口，或双向通信接口，并且可用于发送和接收消息等，以建立连接，确认并交换与通信链路和/或例如编码后的图像数据传输等数据传输相关的任何其他信息，等等。
视频解码器(或解码器)30用于接收编码图像数据21并提供解码图像数据(或解码图像数据)31(下面将根据图3等进一步描述)。
后处理器32用于对解码后的图像等解码图像数据31(也称为重建后的图像数据)进行后处理，得到后处理后的图像等后处理图像数据33。后处理单元32执行的后处理可以包括例如颜色格式转换(例如从YCbCr转换为RGB)、调色、修剪或重采样，或者用于产生供显示设备34等显示的解码图像数据31等任何其他处理。
显示设备34用于接收后处理图像数据33，以向用户或观看者等显示图像。显示设备34可以为或包括任意类型的用于表示重建后图像的显示器，例如，集成或外部显示屏或显示器。例如，显示屏可包括液晶显示器(liquid crystal display，LCD)、有机发光二极管(organic light emitting diode，OLED)显示器、等离子显示器、投影仪、微型LED显示器、硅基液晶显示器(liquid crystal on silicon，LCoS)、数字光处理器(digital light processor，DLP)或任意类型的其他显示屏。
编解码***10还包括训练引擎25，训练引擎25用于训练编码器20(尤其是编码器20中的熵编码单元270)或解码器30(尤其是解码器30中的熵解码单元304)，以根据估计得到的估计概率分布对待编码图像块进行熵编码，训练引擎25的详细说明请参考下 述方法测实施例。
尽管图1a示出了源设备12和目的设备14作为独立的设备，但设备实施例也可以同时包括源设备12和目的设备14或同时包括源设备12和目的设备14的功能，即同时包括源设备12或对应功能和目的设备14或对应功能。在这些实施例中，源设备12或对应功能和目的设备14或对应功能可以使用相同硬件和/或软件或通过单独的硬件和/或软件或其任意组合来实现。
根据描述，图1a所示的源设备12和/或目的设备14中的不同单元或功能的存在和(准确)划分可能根据实际设备和应用而有所不同，这对技术人员来说是显而易见的。
请参考图1b，图1b为本申请实施例提供的视频编解码***40的一种示例性框图，编码器20(例如视频编码器20)或解码器30(例如视频解码器30)或两者都可通过如图1b所示的视频编解码***40中的处理电路实现，例如一个或多个微处理器、数字信号处理器(digital signal processor，DSP)、专用集成电路(application-specific integrated circuit，ASIC)、现场可编程门阵列(field-programmable gate array，FPGA)、离散逻辑、硬件、视频编码专用处理器或其任意组合。请参考图2和图3，图2为本申请实施例提供的视频编码器的一种示例性框图，图3为本申请实施例提供的视频解码器的一种示例性框图。编码器20可以通过处理电路46实现，以包含参照图2编码器20论述的各种模块和/或本文描述的任何其他编码器***或子***。解码器30可以通过处理电路46实现，以包含参照图3解码器30论述的各种模块和/或本文描述的任何其他解码器***或子***。所述处理电路46可用于执行下文论述的各种操作。如图5所示，如果部分技术在软件中实施，则设备可以将软件的指令存储在合适的非瞬时性计算机可读存储介质中，并且使用一个或多个处理器在硬件中执行指令，从而执行本申请实施例技术。视频编码器20和视频解码器30中的其中一个可作为组合编解码器(encoder/decoder，CODEC)的一部分集成在单个设备中，如图1b所示。
源设备12和目的设备14可包括各种设备中的任一种，包括任意类型的手持设备或固定设备，例如，笔记本电脑或膝上型电脑、手机、智能手机、平板或平板电脑、相机、台式计算机、机顶盒、电视机、显示设备、数字媒体播放器、视频游戏控制台、视频流设备(例如，内容业务服务器或内容分发服务器)、广播接收设备、广播发射设备以及监控设备等等，并可以不使用或使用任意类型的操作***。源设备12和目的设备14也可以是云计算场景中的设备，例如云计算场景中的虚拟机等。在一些情况下，源设备12和目的设备14可配备用于无线通信的组件。因此，源设备12和目的设备14可以是无线通信设备。
源设备12和目的设备14可以安装虚拟现实(virtual reality，VR)应用、增强现实(augmented reality，AR)应用或者混合现实(mixed reality，MR)应用等虚拟场景应用程序(application，APP)，并可以基于用户的操作(例如点击、触摸、滑动、抖动、声控等)运行VR应用、AR应用或者MR应用。源设备12和目的设备14可以通过摄像头和/或传感器采集环境中任意物体的图像/视频，再根据采集的图像/视频在显示设备上显示虚拟物体，该虚拟物体可以是VR场景、AR场景或MR场景中的虚拟物体(即虚拟环境中的物体)。
需要说明的是，本申请实施例中，源设备12和目的设备14中的虚拟场景应用程序可以是源设备12和目的设备14自身内置的应用程序，也可以是用户自行安装的第三方服务 商提供的应用程序，对此不做具体限定。
此外，源设备12和目的设备14可以安装实时视频传输应用，例如直播应用。源设备12和目的设备14可以通过摄像头采集图像/视频，再将采集的图像/视频在显示设备上显示。
在一些情况下，图1a所示的视频编解码***10仅仅是示例性的，本申请实施例提供的技术可适用于视频编码设置(例如，视频编码或视频解码)，这些设置不一定包括编码设备与解码设备之间的任何数据通信。在其他示例中，数据从本地存储器中检索，通过网络发送，等等。视频编码设备可以对数据进行编码并将数据存储到存储器中，和/或视频解码设备可以从存储器中检索数据并对数据进行解码。在一些示例中，编码和解码由相互不通信而只是编码数据到存储器和/或从存储器中检索并解码数据的设备来执行。
请参考图1b，图1b为本申请实施例提供的视频编解码***40的一种示例性框图，如图1b所示，视频编解码***40可以包含成像设备41、视频编码器20、视频解码器30(和/或藉由处理电路46实施的视频编/解码器)、天线42、一个或多个处理器43、一个或多个内存存储器44和/或显示设备45。
如图1b所示，成像设备41、天线42、处理电路46、视频编码器20、视频解码器30、处理器43、内存存储器44和/或显示设备45能够互相通信。在不同实例中，视频编解码***40可以只包含视频编码器20或只包含视频解码器30。
在一些实例中，天线42可以用于传输或接收视频数据的经编码比特流。另外，在一些实例中，显示设备45可以用于呈现视频数据。处理电路46可以包含专用集成电路(application-specific integrated circuit，ASIC)逻辑、图形处理器、通用处理器等。视频编解码***40也可以包含可选的处理器43，该可选处理器43类似的可以包含专用集成电路(application-specific integrated circuit，ASIC)逻辑、图形处理器、通用处理器等。另外，内存存储器44可以是任何类型的存储器，例如易失性存储器(例如，静态随机存取存储器(static random access memory，SRAM)、动态随机存储器(dynamic random access memory，DRAM)等)或非易失性存储器(例如，闪存等)等。在非限制性实例中，内存存储器44可以由超速缓存内存实施。在其他实例中，处理电路46可以包含存储器(例如，缓存等)用于实施图像缓冲器等。
在一些实例中，通过逻辑电路实施的视频编码器20可以包含(例如，通过处理电路46或内存存储器44实施的)图像缓冲器和(例如，通过处理电路46实施的)图形处理单元。图形处理单元可以通信耦合至图像缓冲器。图形处理单元可以包含通过处理电路46实施的视频编码器20，以实施参照图2和/或本文中所描述的任何其他编码器***或子***所论述的各种模块。逻辑电路可以用于执行本文所论述的各种操作。
在一些实例中，视频解码器30可以以类似方式通过处理电路46实施，以实施参照图3的视频解码器30和/或本文中所描述的任何其他解码器***或子***所论述的各种模块。在一些实例中，逻辑电路实施的视频解码器30可以包含(通过处理电路46或内存存储器44实施的)图像缓冲器和(例如，通过处理电路46实施的)图形处理单元。图形处理单元可以通信耦合至图像缓冲器。图形处理单元可以包含通过处理电路46实施的视频解码器30，以实施参照图3和/或本文中所描述的任何其他解码器***或子***所论述的各种模块。
在一些实例中，天线42可以用于接收视频数据的经编码比特流。如所论述，经编码比特流可以包含本文所论述的与编码视频帧相关的数据、指示符、索引值、模式选择数据等，例如与编码分割相关的数据(例如，变换系数或经量化变换系数，(如所论述的)可选指示符，和/或定义编码分割的数据)。视频编解码***40还可包含耦合至天线42并用于解码经编码比特流的视频解码器30。显示设备45用于呈现视频帧。
应理解，本申请实施例中对于参考视频编码器20所描述的实例，视频解码器30可以用于执行相反过程。关于信令语法元素，视频解码器30可以用于接收并解析这种语法元素，相应地解码相关视频数据。在一些例子中，视频编码器20可以将语法元素熵编码成经编码视频比特流。在此类实例中，视频解码器30可以解析这种语法元素，并相应地解码相关视频数据。
为便于描述，参考通用视频编码(versatile video coding，VVC)参考软件或由ITU-T视频编码专家组(video coding experts group，VCEG)和ISO/IEC运动图像专家组(motion picture experts group，MPEG)的视频编码联合工作组(joint collaboration team on video coding，JCT-VC)开发的高性能视频编码(high-efficiency video coding，HEVC)描述本申请实施例。本领域普通技术人员理解本申请实施例不限于HEVC或VVC。
编码器和编码方法
如图2所示，视频编码器20包括输入端(或输入接口)201、残差计算单元204、变换处理单元206、量化单元208、反量化单元210、逆变换处理单元212、重建单元214、环路滤波器220、解码图像缓冲器(decoded picture buffer，DPB)230、模式选择单元260、熵编码单元270和输出端(或输出接口)272。模式选择单元260可包括帧间预测单元244、帧内预测单元254和分割单元262。帧间预测单元244可包括运动估计单元和运动补偿单元(未示出)。图2所示的视频编码器20也可称为混合型视频编码器或基于混合型视频编解码器的视频编码器。
参见图2，帧间预测单元为经过训练的目标模型(亦称为神经网络)，该神经网络用于处理输入图像或图像区域或图像块，以生成输入图像块的预测值。例如，用于帧间预测的神经网络用于接收输入的图像或图像区域或图像块，并且生成输入的图像或图像区域或图像块的预测值。
残差计算单元204、变换处理单元206、量化单元208和模式选择单元260组成编码器20的前向信号路径，而反量化单元210、逆变换处理单元212、重建单元214、缓冲器216、环路滤波器220、解码图像缓冲器(decoded picture buffer，DPB)230、帧间预测单元244和帧内预测单元254组成编码器的后向信号路径，其中编码器20的后向信号路径对应于解码器的信号路径(参见图3中的解码器30)。反量化单元210、逆变换处理单元212、重建单元214、环路滤波器220、解码图像缓冲器230、帧间预测单元244和帧内预测单元254还组成视频编码器20的“内置解码器”。
图像和图像分割(图像和块)
编码器20可用于通过输入端201等接收图像(或图像数据)17，例如，形成视频或视频序列的图像序列中的图像。接收的图像或图像数据也可以是预处理后的图像(或预处理后的图像数据)19。为简单起见，以下描述使用图像17。图像17也可称为当前图像或待编码的图像(尤其是在视频编码中将当前图像与其他图像区分开时，其它图像例如同一 视频序列，即也包括当前图像的视频序列，中的之前编码后图像和/或解码后图像)。
(数字)图像为或可以视为具有强度值的像素点组成的二维阵列或矩阵。阵列中的像素点也可以称为像素(pixel或pel)(图像元素的简称)。阵列或图像在水平方向和垂直方向(或轴线)上的像素点数量决定了图像的大小和/或分辨率。为了表示颜色，通常采用三个颜色分量，即图像可以表示为或包括三个像素点阵列。在RBG格式或颜色空间中，图像包括对应的红色、绿色和蓝色像素点阵列。但是，在视频编码中，每个像素通常以亮度/色度格式或颜色空间表示，例如YCbCr，包括Y指示的亮度分量(有时也用L表示)以及Cb、Cr表示的两个色度分量。亮度(luma)分量Y表示亮度或灰度水平强度(例如，在灰度等级图像中两者相同)，而两个色度(chrominance，简写为chroma)分量Cb和Cr表示色度或颜色信息分量。相应地，YCbCr格式的图像包括亮度像素点值(Y)的亮度像素点阵列和色度值(Cb和Cr)的两个色度像素点阵列。RGB格式的图像可以转换或变换为YCbCr格式，反之亦然，该过程也称为颜色变换或转换。如果图像是黑白的，则该图像可以只包括亮度像素点阵列。相应地，图像可以为例如单色格式的亮度像素点阵列或4:2:0、4:2:2和4:4:4彩色格式的亮度像素点阵列和两个相应的色度像素点阵列。
在一个实施例中，视频编码器20的实施例可包括图像分割单元(图2中未示出)，用于将图像17分割成多个(通常不重叠)图像块203。这些块在H.265/HEVC和VVC标准中也可以称为根块、宏块(H.264/AVC)或编码树块(coding tree block，CTB)，或编码树单元(coding tree unit，CTU)。分割单元可用于对视频序列中的所有图像使用相同的块大小和使用限定块大小的对应网格，或在图像或图像子集或图像组之间改变块大小，并将每个图像分割成对应块。
在其他实施例中，视频编码器可用于直接接收图像17的块203，例如，组成所述图像17的一个、几个或所有块。图像块203也可以称为当前图像块或待编码图像块。
与图像17一样，图像块203同样是或可认为是具有强度值(像素点值)的像素点组成的二维阵列或矩阵，但是图像块203的比图像17的小。换句话说，块203可包括一个像素点阵列(例如，单色图像17情况下的亮度阵列或彩色图像情况下的亮度阵列或色度阵列)或三个像素点阵列(例如，彩色图像17情况下的一个亮度阵列和两个色度阵列)或根据所采用的颜色格式的任何其他数量和/或类型的阵列。块203的水平方向和垂直方向(或轴线)上的像素点数量限定了块203的大小。相应地，块可以为M×N(M列×N行)个像素点阵列，或M×N个变换系数阵列等。
在一个实施例中，图2所示的视频编码器20用于逐块对图像17进行编码，例如，对每个块203执行编码和预测。
在一个实施例中，图2所示的视频编码器20还可以用于使用片(也称为视频片)分割和/或编码图像，其中图像可以使用一个或多个片(通常为不重叠的)进行分割或编码。每个片可包括一个或多个块(例如，编码树单元CTU)或一个或多个块组(例如H.265/HEVC/VVC标准中的编码区块(tile)和VVC标准中的砖(brick)。
在一个实施例中，图2所示的视频编码器20还可以用于使用片/编码区块组(也称为视频编码区块组)和/或编码区块(也称为视频编码区块)对图像进行分割和/或编码，其中图像可以使用一个或多个片/编码区块组(通常为不重叠的)进行分割或编码，每个片/编码区块组可包括一个或多个块(例如CTU)或一个或多个编码区块等，其中每个编码 区块可以为矩形等形状，可包括一个或多个完整或部分块(例如CTU)。
残差计算
残差计算单元204用于通过如下方式根据图像块(或原始块)203和预测块265来计算残差块205(后续详细介绍了预测块265)：例如，逐个像素点(逐个像素)从图像块203的像素点值中减去预测块265的像素点值，得到像素域中的残差块205。
变换
变换处理单元206用于对残差块205的像素点值执行离散余弦变换(discrete cosine transform，DCT)或离散正弦变换(discrete sine transform，DST)等，得到变换域中的变换系数207。变换系数207也可称为变换残差系数，表示变换域中的残差块205。
变换处理单元206可用于应用DCT/DST的整数化近似，例如为H.265/HEVC指定的变换。与正交DCT变换相比，这种整数化近似通常由某一因子按比例缩放。为了维持经过正变换和逆变换处理的残差块的范数，使用其他比例缩放因子作为变换过程的一部分。比例缩放因子通常是根据某些约束条件来选择的，例如比例缩放因子是用于移位运算的2的幂、变换系数的位深度、准确性与实施成本之间的权衡等。例如，在编码器20侧通过逆变换处理单元212为逆变换(以及在解码器30侧通过例如逆变换处理单元312为对应逆变换)指定具体的比例缩放因子，以及相应地，可以在编码器20侧通过变换处理单元206为正变换指定对应比例缩放因子。
在一个实施例中，视频编码器20(对应地，变换处理单元206)可用于输出一种或多种变换的类型等变换参数，例如，直接输出或由熵编码单元270进行编码或压缩后输出，例如使得视频解码器30可接收并使用变换参数进行解码。
量化
量化单元208用于通过例如标量量化或矢量量化对变换系数207进行量化，得到量化变换系数209。量化变换系数209也可称为量化残差系数209。
量化过程可减少与部分或全部变换系数207有关的位深度。例如，可在量化期间将n位变换系数向下舍入到m位变换系数，其中n大于m。可通过调整量化参数(quantization parameter，QP)修改量化程度。例如，对于标量量化，可以应用不同程度的比例来实现较细或较粗的量化。较小量化步长对应较细量化，而较大量化步长对应较粗量化。可通过量化参数(quantization parameter，QP)指示合适的量化步长。例如，量化参数可以为合适的量化步长的预定义集合的索引。例如，较小的量化参数可对应精细量化(较小量化步长)，较大的量化参数可对应粗糙量化(较大量化步长)，反之亦然。量化可包括除以量化步长，而反量化单元210等执行的对应或逆解量化可包括乘以量化步长。根据例如HEVC一些标准的实施例可用于使用量化参数来确定量化步长。一般而言，可以根据量化参数使用包含除法的等式的定点近似来计算量化步长。可以引入其他比例缩放因子来进行量化和解量化，以恢复可能由于在用于量化步长和量化参数的等式的定点近似中使用的比例而修改的残差块的范数。在一种示例性实现方式中，可以合并逆变换和解量化的比例。或者，可以使用自定义量化表并在比特流中等将其从编码器向解码器指示。量化是有损操作，其中量化步长越大，损耗越大。
在一个实施例中，视频编码器20(对应地，量化单元208)可用于输出量化参数(quantization parameter，QP)，例如，直接输出或由熵编码单元270进行编码或压缩后 输出，例如使得视频解码器30可接收并使用量化参数进行解码。
反量化
反量化单元210用于对量化系数执行量化单元208的反量化，得到解量化系数211，例如，根据或使用与量化单元208相同的量化步长执行与量化单元208所执行的量化方案的反量化方案。解量化系数211也可称为解量化残差系数211，对应于变换系数207，但是由于量化造成损耗，反量化系数211通常与变换系数不完全相同。
逆变换
逆变换处理单元212用于执行变换处理单元206执行的变换的逆变换，例如，逆离散余弦变换(discrete cosine transform，DCT)或逆离散正弦变换(discrete sine transform，DST)，以在像素域中得到重建残差块213(或对应的解量化系数213)。重建残差块213也可称为变换块213。
重建
重建单元214(例如，求和器214)用于将变换块213(即重建残差块213)添加到预测块265，以在像素域中得到重建块215，例如，将重建残差块213的像素点值和预测块265的像素点值相加。
滤波
环路滤波器单元220(或简称“环路滤波器”220)用于对重建块215进行滤波，得到滤波块221，或通常用于对重建像素点进行滤波以得到滤波像素点值。例如，环路滤波器单元用于顺利进行像素转变或提高视频质量。环路滤波器单元220可包括一个或多个环路滤波器，例如去块滤波器、像素点自适应偏移(sample-adaptive offset，SAO)滤波器或一个或多个其他滤波器，例如自适应环路滤波器(adaptive loop filter，ALF)、噪声抑制滤波器(noise suppression filter，NSF)或任意组合。例如，环路滤波器单元220可以包括去块滤波器、SAO滤波器和ALF滤波器。滤波过程的顺序可以是去块滤波器、SAO滤波器和ALF滤波器。再例如，增加一个称为具有色度缩放的亮度映射(luma mapping with chroma scaling，LMCS)(即自适应环内整形器)的过程。该过程在去块之前执行。再例如，去块滤波过程也可以应用于内部子块边缘，例如仿射子块边缘、ATMVP子块边缘、子块变换(sub-block transform，SBT)边缘和内子部分(intra sub-partition，ISP)边缘。尽管环路滤波器单元220在图2中示为环路滤波器，但在其他配置中，环路滤波器单元220可以实现为环后滤波器。滤波块221也可称为滤波重建块221。
在一个实施例中，视频编码器20(对应地，环路滤波器单元220)可用于输出环路滤波器参数(例如SAO滤波参数、ALF滤波参数或LMCS参数)，例如，直接输出或由熵编码单元270进行熵编码后输出，例如使得解码器30可接收并使用相同或不同的环路滤波器参数进行解码。
解码图像缓冲器
解码图像缓冲器(decoded picture buffer，DPB)230可以是存储参考图像数据以供视频编码器20在编码视频数据时使用的参考图像存储器。DPB 230可以由多种存储器设备中的任一种形成，例如动态随机存取存储器(dynamic random access memory，DRAM)，包括同步DRAM(synchronous DRAM，SDRAM)、磁阻RAM(magnetoresistive RAM，MRAM)、电阻RAM(resistive RAM，RRAM)或其他类型的存储设备。解码图像缓冲 器230可用于存储一个或多个滤波块221。解码图像缓冲器230还可用于存储同一当前图像或例如之前的重建图像等不同图像的其他之前的滤波块，例如之前重建和滤波的块221，并可提供完整的之前重建即解码图像(和对应参考块和像素点)和/或部分重建的当前图像(和对应参考块和像素点)，例如用于帧间预测。解码图像缓冲器230还可用于存储一个或多个未经滤波的重建块215，或一般存储未经滤波的重建像素点，例如，未被环路滤波单元220滤波的重建块215，或未进行任何其他处理的重建块或重建像素点。
模式选择(分割和预测)
模式选择单元260包括分割单元262、帧间预测单元244和帧内预测单元254，用于从解码图像缓冲器230或其他缓冲器(例如，列缓冲器，图2中未显示)接收或获得原始块203(当前图像17的当前块203)和重建图像数据等原始图像数据，例如，同一(当前)图像和/或一个或多个之前解码图像的滤波和/或未经滤波的重建像素点或重建块。重建图像数据用作帧间预测或帧内预测等预测所需的参考图像数据，以得到预测块265或预测值265。
模式选择单元260可用于为当前块(包括不分割)和预测模式(例如帧内或帧间预测模式)确定或选择一种分割，生成对应的预测块265，以对残差块205进行计算和对重建块215进行重建。
在一个实施例中，模式选择单元260可用于选择分割和预测模式(例如，从模式选择单元260支持的或可用的预测模式中)，所述预测模式提供最佳匹配或者说最小残差(最小残差是指传输或存储中更好的压缩)，或者提供最小信令开销(最小信令开销是指传输或存储中更好的压缩)，或者同时考虑或平衡以上两者。模式选择单元260可用于根据码率失真优化(rate distortion Optimization，RDO)确定分割和预测模式，即选择提供最小码率失真优化的预测模式。本文“最佳”、“最低”、“最优”等术语不一定指总体上“最佳”、“最低”、“最优”的，但也可以指满足终止或选择标准的情况，例如，超过或低于阈值的值或其他限制可能导致“次优选择”，但会降低复杂度和处理时间。
换言之，分割单元262可用于将视频序列中的图像分割为编码树单元(coding tree unit，CTU)序列，CTU 203可进一步被分割成较小的块部分或子块(再次形成块)，例如，通过迭代使用四叉树(quad-tree partitioning，QT)分割、二叉树(binary-tree partitioning，BT)分割或三叉树(triple-tree partitioning，TT)分割或其任意组合，并且用于例如对块部分或子块中的每一个执行预测，其中模式选择包括选择分割块203的树结构和选择应用于块部分或子块中的每一个的预测模式。
下文将详细地描述由视频编码器20执行的分割(例如，由分割单元262执行)和预测处理(例如，由帧间预测单元244和帧内预测单元254执行)。
分割
分割单元262可将一个图像块(或CTU)203分割(或划分)为较小的部分，例如正方形或矩形形状的小块。对于具有三个像素点阵列的图像，一个CTU由N×N个亮度像素点块和两个对应的色度像素点块组成。CTU中亮度块的最大允许大小在正在开发的通用视频编码(versatile video coding，VVC)标准中被指定为128×128，但是将来可指定为不同于128×128的值，例如256×256。图像的CTU可以集中/分组为片/编码区块组、编码区块或砖。一个编码区块覆盖着一个图像的矩形区域，一个编码区块可以分成一个或多个砖。 一个砖由一个编码区块内的多个CTU行组成。没有分割为多个砖的编码区块可以称为砖。但是，砖是编码区块的真正子集，因此不称为编码区块。VVC支持两种编码区块组模式，分别为光栅扫描片/编码区块组模式和矩形片模式。在光栅扫描编码区块组模式，一个片/编码区块组包含一个图像的编码区块光栅扫描中的编码区块序列。在矩形片模式中，片包含一个图像的多个砖，这些砖共同组成图像的矩形区域。矩形片内的砖按照片的砖光栅扫描顺序排列。这些较小块(也可称为子块)可进一步分割为更小的部分。这也称为树分割或分层树分割，其中在根树级别0(层次级别0、深度0)等的根块可以递归的分割为两个或两个以上下一个较低树级别的块，例如树级别1(层次级别1、深度1)的节点。这些块可以又分割为两个或两个以上下一个较低级别的块，例如树级别2(层次级别2、深度2)等，直到分割结束(因为满足结束标准，例如达到最大树深度或最小块大小)。未进一步分割的块也称为树的叶块或叶节点。分割为两个部分的树称为二叉树(binary-tree，BT)，分割为三个部分的树称为三叉树(ternary-tree，TT)，分割为四个部分的树称为四叉树(quad-tree，QT)。
例如，编码树单元(CTU)可以为或包括亮度像素点的CTB、具有三个像素点阵列的图像的色度像素点的两个对应CTB或单色图像的像素点的CTB或使用三个独立颜色平面和语法结构(用于编码像素点)编码的图像的像素点的CTB。相应地，编码树块(CTB)可以为N×N个像素点块，其中N可以设为某个值使得分量划分为CTB，这就是分割。编码单元(coding unit，CU)可以为或包括亮度像素点的编码块、具有三个像素点阵列的图像的色度像素点的两个对应编码块或单色图像的像素点的编码块或使用三个独立颜色平面和语法结构(用于编码像素点)编码的图像的像素点的编码块。相应地，编码块(CB)可以为M×N个像素点块，其中M和N可以设为某个值使得CTB划分为编码块，这就是分割。
例如，在实施例中，根据HEVC可通过使用表示为编码树的四叉树结构将编码树单元(CTU)划分为多个CU。在叶CU级作出是否使用帧间(时间)预测或帧内(空间)预测对图像区域进行编码的决定。每个叶CU可以根据PU划分类型进一步划分为一个、两个或四个PU。一个PU内使用相同的预测过程，并以PU为单位向解码器传输相关信息。在根据PU划分类型应用预测过程得到残差块之后，可以根据类似于用于CU的编码树的其他四叉树结构将叶CU分割为变换单元(TU)。
例如，在实施例中，根据当前正在开发的最新视频编码标准(称为通用视频编码(VVC)，使用嵌套多类型树(例如二叉树和三叉树)的组合四叉树来划分用于分割编码树单元的分段结构。在编码树单元内的编码树结构中，CU可以为正方形或矩形。例如，编码树单元(CTU)首先由四叉树结构进行分割。四叉树叶节点进一步由多类型树结构分割。多类型树形结构有四种划分类型：垂直二叉树划分(SPLIT_BT_VER)、水平二叉树划分(SPLIT_BT_HOR)、垂直三叉树划分(SPLIT_TT_VER)和水平三叉树划分(SPLIT_TT_HOR)。多类型树叶节点称为编码单元(CU)，除非CU对于最大变换长度而言太大，这样的分段用于预测和变换处理，无需其他任何分割。在大多数情况下，这表示CU、PU和TU在四叉树嵌套多类型树的编码块结构中的块大小相同。当最大支持变换长度小于CU的彩色分量的宽度或高度时，就会出现该异常。VVC制定了具有四叉树嵌套多类型树的编码结构中的分割划分信息的唯一信令机制。在信令机制中，编码树单元 (CTU)作为四叉树的根首先被四叉树结构分割。然后每个四叉树叶节点(当足够大可以被)被进一步分割为一个多类型树结构。在多类型树结构中，通过第一标识(mtt_split_cu_flag)指示节点是否进一步分割，当对节点进一步分割时，先用第二标识(mtt_split_cu_vertical_flag)指示划分方向，再用第三标识(mtt_split_cu_binary_flag)指示划分是二叉树划分或三叉树划分。根据mtt_split_cu_vertical_flag和mtt_split_cu_binary_flag的值，解码器可以基于预定义规则或表格推导出CU的多类型树划分模式(MttSplitMode)。需要说明的是，对于某种设计，例如VVC硬件解码器中的64×64的亮度块和32×32的色度流水线设计，当亮度编码块的宽度或高度大于64时，不允许进行TT划分。当色度编码块的宽度或高度大于32时，也不允许TT划分。流水线设计将图像分为多个虚拟流水线数据单元(virtual pipeline data unit，VPDU)，每个VPDU在图像中定义为互不重叠的单元。在硬件解码器中，连续的VPDU在多个流水线阶段同时处理。在大多数流水线阶段，VPDU大小与缓冲器大小大致成正比，因此需要保持较小的VPDU。在大多数硬件解码器中，VPDU大小可以设置为最大变换块(transform block，TB)大小。但是，在VVC中，三叉树(TT)和二叉树(BT)的分割可能会增加VPDU的大小。
另外，需要说明的是，当树节点块的一部分超出底部或图像右边界时，强制对该树节点块进行划分，直到每个编码CU的所有像素点都位于图像边界内。
例如，所述帧内子分割(intra sub-partitions，ISP)工具可以根据块大小将亮度帧内预测块垂直或水平的分为两个或四个子部分。
在一个示例中，视频编码器20的模式选择单元260可以用于执行上文描述的分割技术的任意组合。
如上所述，视频编码器20用于从(预定的)预测模式集合中确定或选择最好或最优的预测模式。预测模式集合可包括例如帧内预测模式和/或帧间预测模式。
帧内预测
帧内预测模式集合可包括35种不同的帧内预测模式，例如，像DC(或均值)模式和平面模式的非方向性模式，或如HEVC定义的方向性模式，或者可包括67种不同的帧内预测模式，例如，像DC(或均值)模式和平面模式的非方向性模式，或如VVC中定义的方向性模式。例如，若干传统角度帧内预测模式自适应地替换为VVC中定义的非正方形块的广角帧内预测模式。又例如，为了避免DC预测的除法运算，仅使用较长边来计算非正方形块的平均值。并且，平面模式的帧内预测结果还可以使用位置决定的帧内预测组合(position dependent intra prediction combination，PDPC)方法修改。
帧内预测单元254用于根据帧内预测模式集合中的帧内预测模式使用同一当前图像的相邻块的重建像素点来生成帧内预测块265。
帧内预测单元254(或通常为模式选择单元260)还用于输出帧内预测参数(或通常为指示块的选定帧内预测模式的信息)以语法元素266的形式发送到熵编码单元270，以包含到编码图像数据21中，从而视频解码器30可执行操作，例如接收并使用用于解码的预测参数。
HEVC中的帧内预测模式包括直流预测模式，平面预测模式和33种角度预测模式，共计35个候选预测模式。当前块可以使用左侧和上方已重建图像块的像素作为参考进行 帧内预测。当前块的周边区域中用来对当前块进行帧内预测的图像块成为参考块，参考块中的像素称为参考像素。35个候选预测模式中，直流预测模式适用于当前块中纹理平坦的区域，该区域中所有像素均使用参考块中的参考像素的平均值作为预测；平面预测模式适用于纹理平滑变化的图像块，符合该条件的当前块使用参考块中的参考像素进行双线性插值作为当前块中的所有像素的预测；角度预测模式利用当前块的纹理与相邻已重建图像块的纹理高度相关的特性，沿某一角度复制对应的参考块中的参考像素的值作为当前块中的所有像素的预测。
HEVC编码器给当前块从35个候选预测模式中选择一个最优帧内预测模式，并将该最优帧内预测模式写入视频码流。为提升帧内预测的编码效率，编码器/解码器会从周边区域中、采用帧内预测的已重建图像块各自的最优帧内预测模式中推导出3个最可能模式，如果给当前块选择的最优帧内预测模式是这3个最可能模式的其中之一，则编码一个第一索引指示所选择的最优帧内预测模式是这3个最可能模式的其中之一；如果选中的最优帧内预测模式不是这3个最可能模式，则编码一个第二索引指示所选择的最优帧内预测模式是其他32个模式(35个候选预测模式中除前述3个最可能模式外的其他模式)的其中之一。HEVC标准使用5比特的定长码作为前述第二索引。
HEVC编码器推导出3个最可能模式的方法包括：选取当前块的左相邻图像块和上相邻图像块的最优帧内预测模式放入集合，如果这两个最优帧内预测模式相同，则集合中只保留一个即可。如果这两个最优帧内预测模式相同且均为角度预测模式，则再选取与该角度方向邻近的两个角度预测模式加入集合；否则，依次选择平面预测模式、直流模式和竖直预测模式加入集合，直到集合中的模式数量达到3。
HEVC解码器对码流做熵解码后，获得当前块的模式信息，该模式信息包括指示当前块的最优帧内预测模式是否在3个最可能模式中的指示标识，以及当前块的最优帧内预测模式在3个最可能模式中的索引或者当前块的最优帧内预测模式在其他32个模式中的索引。
帧间预测
在可能的实现中，帧间预测模式集合取决于可用参考图像(即，例如前述存储在DBP230中的至少部分之前解码的图像)和其他帧间预测参数，例如取决于是否使用整个参考图像或只使用参考图像的一部分，例如当前块的区域附近的搜索窗口区域，来搜索最佳匹配参考块，和/或例如取决于是否执行半像素、四分之一像素和/或16分之一内插的像素内插。
除上述预测模式外，还可以采用跳过模式和/或直接模式。
例如，扩展合并预测，这个模式的合并候选列表由以下五个候选类型按顺序组成：来自空间相邻CU的空间MVP、来自并置CU的时间MVP、来自FIFO表的基于历史的MVP、成对平均MVP和零MV。可以使用基于双边匹配的解码器侧运动矢量修正(decoder side motion vector refinement，DMVR)来增加合并模式的MV的准确度。带有MVD的合并模式(merge mode with MVD，MMVD)来自有运动矢量差异的合并模式。在发送跳过标志和合并标志之后立即发送MMVD标志，以指定CU是否使用MMVD模式。可以使用CU级自适应运动矢量分辨率(adaptive motion vector resolution，AMVR)方案。AMVR支持CU的MVD以不同的精度进行编码。根据当前CU的预测模式，自适应地选择当前CU 的MVD。当CU以合并模式进行编码时，可以将合并的帧间/帧内预测(combined inter/intra prediction，CIIP)模式应用于当前CU。对帧间和帧内预测信号进行加权平均，得到CIIP预测。对于仿射运动补偿预测，通过2个控制点(4参数)或3个控制点(6参数)运动矢量的运动信息来描述块的仿射运动场。基于子块的时间运动矢量预测(subblock-based temporal motion vector prediction，SbTMVP)，与HEVC中的时间运动矢量预测(temporal motion vector prediction，TMVP)类似，但预测的是当前CU内的子CU的运动矢量。双向光流(bi-directional optical flow，BDOF)以前称为BIO，是一种减少计算的简化版本，特别是在乘法次数和乘数大小方面的计算。在三角形分割模式中，CU以对角线划分和反对角线划分两种划分方式被均匀划分为两个三角形部分。此外，双向预测模式在简单平均的基础上进行了扩展，以支持两个预测信号的加权平均。
帧间预测单元244可包括运动估计(motion estimation，ME)单元和运动补偿(motion compensation，MC)单元(两者在图2中未示出)。运动估计单元可用于接收或获取图像块203(当前图像17的当前图像块203)和解码图像231，或至少一个或多个之前重建块，例如，一个或多个其它/不同之前解码图像231的重建块，来进行运动估计。例如，视频序列可包括当前图像和之前的解码图像231，或换句话说，当前图像和之前的解码图像231可以为形成视频序列的图像序列的一部分或形成该图像序列。
例如，编码器20可用于从多个其他图像中的同一或不同图像的多个参考块中选择参考块，并将参考图像(或参考图像索引)和/或参考块的位置(x、y坐标)与当前块的位置之间的偏移(空间偏移)作为帧间预测参数提供给运动估计单元。该偏移也称为运动矢量(motion vector，MV)。
运动补偿单元用于获取，例如接收，帧间预测参数，并根据或使用该帧间预测参数执行帧间预测，得到帧间预测块246。由运动补偿单元执行的运动补偿可能包含根据通过运动估计确定的运动/块矢量来提取或生成预测块，还可能包括对子像素精度执行内插。内插滤波可从已知像素的像素点中产生其他像素的像素点，从而潜在地增加可用于对图像块进行编码的候选预测块的数量。一旦接收到当前图像块的PU对应的运动矢量时，运动补偿单元可在其中一个参考图像列表中定位运动矢量指向的预测块。
运动补偿单元还可以生成与块和视频片相关的语法元素，以供视频解码器30在解码视频片的图像块时使用。此外，或者作为片和相应语法元素的替代，可以生成或使用编码区块组和/或编码区块以及相应语法元素。
在获取先进的运动矢量预测(advanced motion vector prediction，AMVP)模式中的候选运动矢量列表的过程中，作为备选可以加入候选运动矢量列表的运动矢量(motion vector，MV)包括当前块的空域相邻和时域相邻的图像块的MV，其中空域相邻的图像块的MV又可以包括位于当前块左侧的左方候选图像块的MV和位于当前块上方的上方候选图像块的MV。示例性的，请参考图4，图4为本申请实施例提供的候选图像块的一种示例性的示意图，如图4所示，左方候选图像块的集合包括{A0，A1}，上方候选图像块的集合包括{B0，B1，B2}，时域相邻的候选图像块的集合包括{C，T}，这三个集合均可以作为备选被加入到候选运动矢量列表中，但是根据现有编码标准，AMVP的候选运动矢量列表的最大长度为2，因此需要根据规定的顺序从三个集合中确定在候选运动矢量列表中加入最多两个图像块的MV。该顺序可以是优先考虑当前块的左方候选图像块的集合{A0，A1} (先考虑A0，A0不可得再考虑A1)，其次考虑当前块的上方候选图像块的集合{B0，B1，B2}(先考虑B0，B0不可得再考虑B1，B1不可得再考虑B2)，最后考虑当前块的时域相邻的候选图像块的集合{C，T}(先考虑T，T不可得再考虑C)。
得到上述候选运动矢量列表后，通过率失真代价(rate distortion cost，RD cost)从候选运动矢量列表中确定最优的MV，将RD cost最小的候选运动矢量作为当前块的运动矢量预测值(motion vector predictor，MVP)。率失真代价由以下公式计算获得：
J＝SAD+λR
其中，J表示RD cost，SAD为使用候选运动矢量进行运动估计后得到的预测块的像素值与当前块的像素值之间的绝对误差和(sum of absolute differences，SAD)，R表示码率，λ表示拉格朗日乘子。
编码端将确定出的MVP在候选运动矢量列表中的索引传递到解码端。进一步地，可以在MVP为中心的邻域内进行运动搜索获得当前块实际的运动矢量，编码端计算MVP与实际的运动矢量之间的运动矢量差值(motion vector difference，MVD)，并将MVD也传递到解码端。解码端解析索引，根据该索引在候选运动矢量列表中找到对应的MVP，解析MVD，将MVD与MVP相加得到当前块实际的运动矢量。
在获取融合(Merge)模式中的候选运动信息列表的过程中，作为备选可以加入候选运动信息列表的运动信息包括当前块的空域相邻或时域相邻的图像块的运动信息，其中空域相邻的图像块和时域相邻的图像块可参照图4，候选运动信息列表中对应于空域的候选运动信息来自于空间相邻的5个块(A0、A1、B0、B1和B2)，若空域相邻块不可得或者为帧内预测，则其运动信息不加入候选运动信息列表。当前块的时域的候选运动信息根据参考帧和当前帧的图序计数(picture order count，POC)对参考帧中对应位置块的MV进行缩放后获得，先判断参考帧中位置为T的块是否可得，若不可得则选择位置为C的块。得到上述候选运动信息列表后，通过RD cost从候选运动信息列表中确定最优的运动信息作为当前块的运动信息。编码端将最优的运动信息在候选运动信息列表中位置的索引值(记为merge index)传递到解码端。
熵编码
熵编码单元270用于将熵编码算法或方案(例如，可变长度编码(variable length coding，VLC)方案、上下文自适应VLC方案(context adaptive VLC，CALVC)、算术编码方案、二值化算法、上下文自适应二进制算术编码(context adaptive binary arithmetic coding，CABAC)、基于语法的上下文自适应二进制算术编码(syntax-based context-adaptive binary arithmetic coding，SBAC)、概率区间分割熵(probability interval partitioning entropy，PIPE)编码或其它熵编码方法或技术)应用于量化残差系数209、帧间预测参数、帧内预测参数、环路滤波器参数和/或其他语法元素，得到可以通过输出端272以编码比特流21等形式输出的编码图像数据21，使得视频解码器30等可以接收并使用用于解码的参数。可将编码比特流21传输到视频解码器30，或将其保存在存储器中稍后由视频解码器30传输或检索。
视频编码器20的其他结构变体可用于对视频流进行编码。例如，基于非变换的编码器20可以在某些块或帧没有变换处理单元206的情况下直接量化残差信号。在另一种实现方式中，编码器20可以具有组合成单个单元的量化单元208和反量化单元210。
解码器和解码方法
如图3所示，视频解码器30用于接收例如由编码器20编码的编码图像数据21(例如编码比特流21)，得到解码图像331。编码图像数据或比特流包括用于解码所述编码图像数据的信息，例如表示编码视频片(和/或编码区块组或编码区块)的图像块的数据和相关的语法元素。
在图3的示例中，解码器30包括熵解码单元304、反量化单元310、逆变换处理单元312、重建单元314(例如求和器314)、环路滤波器320、解码图像缓冲器330、模式应用单元360、帧间预测单元344和帧内预测单元354。帧间预测单元344可以为或包括运动补偿单元。在一些示例中，视频解码器30可执行大体上与参照图2的视频编码器100描述的编码过程相反的解码过程。
如编码器20所述，反量化单元210、逆变换处理单元212、重建单元214、环路滤波器220、解码图像缓冲器DPB230、帧间预测单元344和帧内预测单元354还组成视频编码器20的“内置解码器”。相应地，反量化单元310在功能上可与反量化单元110相同，逆变换处理单元312在功能上可与逆变换处理单元122相同，重建单元314在功能上可与重建单元214相同，环路滤波器320在功能上可与环路滤波器220相同，解码图像缓冲器330在功能上可与解码图像缓冲器230相同。因此，视频编码器20的相应单元和功能的解释相应地适用于视频解码器30的相应单元和功能。
熵解码
熵解码单元304用于解析比特流21(或一般为编码图像数据21)并对编码图像数据21执行熵解码，得到量化系数309和/或解码后的编码参数(图3中未示出)等，例如帧间预测参数(例如参考图像索引和运动矢量)、帧内预测参数(例如帧内预测模式或索引)、变换参数、量化参数、环路滤波器参数和/或其他语法元素等中的任一个或全部。熵解码单元304可用于应用编码器20的熵编码单元270的编码方案对应的解码算法或方案。熵解码单元304还可用于向模式应用单元360提供帧间预测参数、帧内预测参数和/或其他语法元素，以及向解码器30的其他单元提供其他参数。视频解码器30可以接收视频片和/或视频块级的语法元素。此外，或者作为片和相应语法元素的替代，可以接收或使用编码区块组和/或编码区块以及相应语法元素。
反量化
反量化单元310可用于从编码图像数据21(例如通过熵解码单元304解析和/或解码)接收量化参数(quantization parameter，QP)(或一般为与反量化相关的信息)和量化系数，并基于所述量化参数对所述解码的量化系数309进行反量化以获得反量化系数311，所述反量化系数311也可以称为变换系数311。反量化过程可包括使用视频编码器20为视频片中的每个视频块计算的量化参数来确定量化程度，同样也确定需要执行的反量化的程度。
逆变换
逆变换处理单元312可用于接收解量化系数311，也称为变换系数311，并对解量化系数311应用变换以得到像素域中的重建残差块213。重建残差块213也可称为变换块313。变换可以为逆变换，例如逆DCT、逆DST、逆整数变换或概念上类似的逆变换过程。逆变换处理单元312还可以用于从编码图像数据21(例如通过熵解码单元304解析和/或解 码)接收变换参数或相应信息，以确定应用于解量化系数311的变换。
重建
重建单元314(例如，求和器314)用于将重建残差块313添加到预测块365，以在像素域中得到重建块315，例如，将重建残差块313的像素点值和预测块365的像素点值相加。
滤波
环路滤波器单元320(在编码环路中或之后)用于对重建块315进行滤波，得到滤波块321，从而顺利进行像素转变或提高视频质量等。环路滤波器单元320可包括一个或多个环路滤波器，例如去块滤波器、像素点自适应偏移(sample-adaptive offset，SAO)滤波器或一个或多个其他滤波器，例如自适应环路滤波器(adaptive loop filter，ALF)、噪声抑制滤波器(noise suppression filter，NSF)或任意组合。例如，环路滤波器单元220可以包括去块滤波器、SAO滤波器和ALF滤波器。滤波过程的顺序可以是去块滤波器、SAO滤波器和ALF滤波器。再例如，增加一个称为具有色度缩放的亮度映射(luma mapping with chroma scaling，LMCS)(即自适应环内整形器)的过程。该过程在去块之前执行。再例如，去块滤波过程也可以应用于内部子块边缘，例如仿射子块边缘、ATMVP子块边缘、子块变换(sub-block transform，SBT)边缘和内子部分(intra sub-partition，ISP)边缘。尽管环路滤波器单元320在图3中示为环路滤波器，但在其他配置中，环路滤波器单元320可以实现为环后滤波器。
解码图像缓冲器
随后将一个图像中的解码视频块321存储在解码图像缓冲器330中，解码图像缓冲器330存储作为参考图像的解码图像331，参考图像用于其他图像和/或分别输出显示的后续运动补偿。
解码器30用于通过输出端312等输出解码图像311，向用户显示或供用户查看。
预测
帧间预测单元344在功能上可与帧间预测单元244(特别是运动补偿单元)相同，帧内预测单元354在功能上可与帧间预测单元254相同，并基于从编码图像数据21(例如通过熵解码单元304解析和/或解码)接收的分割和/或预测参数或相应信息决定划分或分割和执行预测。模式应用单元360可用于根据重建图像、块或相应的像素点(已滤波或未滤波)执行每个块的预测(帧内或帧间预测)，得到预测块365。
当将视频片编码为帧内编码(intra coded，I)片时，模式应用单元360中的帧内预测单元354用于根据指示的帧内预测模式和来自当前图像的之前解码块的数据生成用于当前视频片的图像块的预测块365。当视频图像编码为帧间编码(即，B或P)片时，模式应用单元360中的帧间预测单元344(例如运动补偿单元)用于根据运动矢量和从熵解码单元304接收的其他语法元素生成用于当前视频片的视频块的预测块365。对于帧间预测，可从其中一个参考图像列表中的其中一个参考图像产生这些预测块。视频解码器30可以根据存储在DPB 330中的参考图像，使用默认构建技术来构建参考帧列表0和列表1。除了片(例如视频片)或作为片的替代，相同或类似的过程可应用于编码区块组(例如视频编码区块组)和/或编码区块(例如视频编码区块)的实施例，例如视频可以使用I、P或B编码区块组和/或编码区块进行编码。
模式应用单元360用于通过解析运动矢量和其他语法元素，确定用于当前视频片的视频块的预测信息，并使用预测信息产生用于正在解码的当前视频块的预测块。例如，模式应用单元360使用接收到的一些语法元素确定用于编码视频片的视频块的预测模式(例如帧内预测或帧间预测)、帧间预测片类型(例如B片、P片或GPB片)、用于片的一个或多个参考图像列表的构建信息、用于片的每个帧间编码视频块的运动矢量、用于片的每个帧间编码视频块的帧间预测状态、其它信息，以解码当前视频片内的视频块。除了片(例如视频片)或作为片的替代，相同或类似的过程可应用于编码区块组(例如视频编码区块组)和/或编码区块(例如视频编码区块)的实施例，例如视频可以使用I、P或B编码区块组和/或编码区块进行编码。
在一个实施例中，图3的视频编码器30还可以用于使用片(也称为视频片)分割和/或解码图像，其中图像可以使用一个或多个片(通常为不重叠的)进行分割或解码。每个片可包括一个或多个块(例如CTU)或一个或多个块组(例如H.265/HEVC/VVC标准中的编码区块和VVC标准中的砖。
在一个实施例中，图3所示的视频解码器30还可以用于使用片/编码区块组(也称为视频编码区块组)和/或编码区块(也称为视频编码区块)对图像进行分割和/或解码，其中图像可以使用一个或多个片/编码区块组(通常为不重叠的)进行分割或解码，每个片/编码区块组可包括一个或多个块(例如CTU)或一个或多个编码区块等，其中每个编码区块可以为矩形等形状，可包括一个或多个完整或部分块(例如CTU)。
视频解码器30的其他变型可用于对编码图像数据21进行解码。例如，解码器30可以在没有环路滤波器单元320的情况下产生输出视频流。例如，基于非变换的解码器30可以在某些块或帧没有逆变换处理单元312的情况下直接反量化残差信号。在另一种实现方式中，视频解码器30可以具有组合成单个单元的反量化单元310和逆变换处理单元312。
应理解，在编码器20和解码器30中，可以对当前步骤的处理结果进一步处理，然后输出到下一步骤。例如，在插值滤波、运动矢量推导或环路滤波之后，可以对插值滤波、运动矢量推导或环路滤波的处理结果进行进一步的运算，例如裁剪(clip)或移位(shift)运算。
应该注意的是，可以对当前块的推导运动矢量(包括但不限于仿射模式的控制点运动矢量、仿射、平面、ATMVP模式的子块运动矢量、时间运动矢量等)进行进一步运算。例如，根据运动矢量的表示位将运动矢量的值限制在预定义范围。如果运动矢量的表示位为bitDepth，则范围为-2^(bitDepth-1)至2^(bitDepth-1)-1，其中“^”表示幂次方。例如，如果bitDepth设置为16，则范围为-32768～32767；如果bitDepth设置为18，则范围为-131072～131071。例如，推导运动矢量的值(例如一个8×8块中的4个4×4子块的MV)被限制，使得所述4个4×4子块MV的整数部分之间的最大差值不超过N个像素，例如不超过1个像素。这里提供了两种根据bitDepth限制运动矢量的方法。
尽管上述实施例主要描述了视频编解码，但应注意的是，编解码***10、编码器20和解码器30的实施例以及本文描述的其他实施例也可以用于静止图像处理或编解码，即视频编解码中独立于任何先前或连续图像的单个图像的处理或编解码。一般情况下，如果图像处理仅限于单个图像17，帧间预测单元244(编码器)和帧间预测单元344(解码器)可能不可用。视频编码器20和视频解码器30的所有其他功能(也称为工具或技术)同样 可用于静态图像处理，例如残差计算204/304、变换206、量化208、反量化210/310、(逆)变换212/312、分割262/362、帧内预测254/354和/或环路滤波220/320、熵编码270和熵解码304。
请参考图5，图5为本申请实施例提供的视频译码设备500的一种示例性框图。视频译码设备500适用于实现本文描述的公开实施例。在一个实施例中，视频译码设备500可以是解码器，例如图1a中的视频解码器30，也可以是编码器，例如图1a中的视频编码器20。
视频译码设备500包括：用于接收数据的入端口510(或输入端口510)和接收单元(receiver unit，Rx)520；用于处理数据的处理器、逻辑单元或中央处理器(central processing unit，CPU)530；例如，这里的处理器530可以是神经网络处理器530；用于传输数据的发送单元(transmitter unit，Tx)540和出端口550(或输出端口550)；用于存储数据的存储器560。视频译码设备500还可包括耦合到入端口510、接收单元520、发送单元540和出端口550的光电(optical-to-electrical，OE)组件和电光(electrical-to-optical，EO)组件，用于光信号或电信号的出口或入口。
处理器530通过硬件和软件实现。处理器530可实现为一个或多个处理器芯片、核(例如，多核处理器)、FPGA、ASIC和DSP。处理器530与入端口510、接收单元520、发送单元540、出端口550和存储器560通信。处理器530包括译码模块570(例如，基于神经网络的译码模块570)。译码模块570实施上文所公开的实施例。例如，译码模块570执行、处理、准备或提供各种编码操作。因此，通过译码模块570为视频译码设备500的功能提供了实质性的改进，并且影响了视频译码设备500到不同状态的切换。或者，以存储在存储器560中并由处理器530执行的指令来实现译码模块570。
存储器560包括一个或多个磁盘、磁带机和固态硬盘，可以用作溢出数据存储设备，用于在选择执行程序时存储此类程序，并且存储在程序执行过程中读取的指令和数据。存储器560可以是易失性和/或非易失性的，可以是只读存储器(read-only memory，ROM)、随机存取存储器(random access memory，RAM)、三态内容寻址存储器(ternary content-addressable memory，TCAM)和/或静态随机存取存储器(static random-access memory，SRAM)。
请参考图6，图6为本申请实施例提供的装置600的一种示例性框图，装置600可用作图1a中的源设备12和目的设备14中的任一个或两个。
装置600中的处理器602可以是中央处理器。或者，处理器602可以是现有的或今后将研发出的能够操控或处理信息的任何其他类型设备或多个设备。虽然可以使用如图所示的处理器602等单个处理器来实施已公开的实现方式，但使用一个以上的处理器速度更快和效率更高。
在一种实现方式中，装置600中的存储器604可以是只读存储器(ROM)设备或随机存取存储器(RAM)设备。任何其他合适类型的存储设备都可以用作存储器604。存储器604可以包括处理器602通过总线612访问的代码和数据606。存储器604还可包括操作***608和应用程序610，应用程序610包括允许处理器602执行本文所述方法的至少一个程序。例如，应用程序610可以包括应用1至N，还包括执行本文所述方法的视频译码应用。
装置600还可以包括一个或多个输出设备，例如显示器618。在一个示例中，显示器618可以是将显示器与可用于感测触摸输入的触敏元件组合的触敏显示器。显示器618可以通过总线612耦合到处理器602。
虽然装置600中的总线612在本文中描述为单个总线，但是总线612可以包括多个总线。此外，辅助储存器可以直接耦合到装置600的其他组件或通过网络访问，并且可以包括存储卡等单个集成单元或多个存储卡等多个单元。因此，装置600可以具有各种各样的配置。
本申请实施例提供的编解码方法可以应用于各种编解码场景。
示例性地，本申请实施例提供的编解码方法可应用到N端(也就是N个设备)协同渲染的场景中，其中，N为大于1的整数。
一种可能的场景中，可以由1个设备生成渲染输入信息(渲染输入信息可以包括三维物体模型(也可以称为3D(3-dimension，三维)物体模型)、探针数据等中的一种或多种，本申请实施例对此不作限制；本申请实施例以渲染输入信息为探针数据为例进行示例性说明)，然后将探针数据分发给其他N-1个设备。N-1个设备接收到的探针数据后，在渲染过程中可以根据探针数据，确定三维场景中对象(与三维物体模型对应)的着色效果；待渲染完成后，可以得到渲染后的图像。
一种可能的场景中，可以由N1(N1的取值范围为2～N，其中，N1可以等于2或N，N1为整数)个设备协同生成探针数据，其中，N1个设备中每个设备生成探针数据的一部分。接着，这N1个设备中每个设备将自身生成的部分探针数据，分发给其他N-1个设备。其中，N1个设备接收到探针数据后，在渲染过程中，可以根据接收到的探针数据和自身生成的部分探针数据，确定三维场景中对象的着色效果；待渲染完成后，可以得到渲染后的图像。N-N1个设备接收到探针数据后，在渲染过程中，可以根据接收到的探针数据，确定三维场景中对象的着色效果；待渲染完成后，可以得到渲染后的图像。
为了便于说明，可以将N端协同渲染场景中生成探针数据的设备，称为第一设备，将用于渲染，且在渲染过程中根据探针数据确定三维场景中对象的着色效果的设备，称为第二设备；一个设备既可以是第一设备，也可以是第二设备，本申请对此不作限制。其中，第一设备可以是服务器，也可以是终端；第二设备可以是终端。
图7a为示例性示出的***框架示意图。在图7a的实施例中，第一设备为布设在云端的计算中心服务器，第二设备为客户端，图7a为示例性示出的端云协同渲染***框架示意图。
参照图7a，示例性地，端云协同渲染***可以包括：计算中心服务器、边缘服务器和客户端；其中，边缘服务器可以包括n(n为大于1的整数)个，客户端可以包括k1+k2+......+kn个，k1、k2......kn，均为正整数。计算中心服务器与n个边缘服务器连接，每个边缘服务器与至少一个客户端连接。如图7a所示，边缘服务器1与客户端11、客户端12、......、客户端k1这k1个客户端连接，边缘服务器2与客户端21、客户端22、......、客户端k2这k2个客户端连接，......，边缘服务器n与客户端n1、客户端n2、......、客户端kn这kn个客户端连接。
示例性地，计算中心服务器可以是一个服务器，也可以是服务器集群，本申请实施例对此不作限制。
示例性地，本申请实施例不限制边缘服务器的数量n，具体可以根据实际应用场景设置，本申请实施例对此不作限制。
示例性地，本申请实施例不限制每个边缘服务器所连接的客户端的数量，具体可以根据实际应用场景设置。此外，每个边缘服务器所连接的客户端的数量可以相同，也可以不同(即k1、k2......kn可以相等，也可以不等)，具体可以根据实际应用场景设置，本申请实施例对此也不作限制。
示例性地，客户端可以包括但不限于：个人电脑、手机、VR(Virtual Reality，虚拟现实)穿戴设备等终端设备。
应该理解的是，图7a所示的端云协同渲染***框架仅是本申请实施例端云协同渲染***框架的一个示例，本申请实施例的端云协同渲染***中，计算中心服务器和边缘服务器可以是同一个服务器；或者本申请实施例的端云协同渲染***不包含边缘服务器，而是计算中心服务器与各客户端连接，本申请实施例对此不作限制。本申请实施例以图7a所示的端云协同渲染***框架为例进行示例性说明。
示例性地，计算中心服务器，可以用于生成探针数据。
示例性地，边缘服务器，可以用于分发探针数据。
示例性地，客户端，可以用于渲染以及显示渲染后的图像；其中，在渲染过程中，可以根据探针数据确定三维场景中对象的着色效果。
示例性地，云游戏、云展览、室内装修、服装设计、建筑设计等多端协同渲染的场景，均可以采用图7a所示的端云协同渲染***框架实现。
例如，云游戏场景中，计算中心服务器接收到客户端11发送的视角切换指示后，可以生成目标视角对应游戏场景的探针数据；然后将探针数据发送给边缘服务器1，由边缘服务器1将该探针数据发送给客户端11。客户端11接收到探针数据后可以进行渲染，以及在渲染过程中根据接收到的探针数据，确定目标视角对应游戏场景中对象的着色效果；待渲染完成后，可以得到目标视角对应游戏场景的图像并显示。
例如，室内装修场景中，计算中心服务器接收到客户端21发送的添加家具指示后，可以生成添加目标家具后的客厅场景对应的探针数据；然后将探针数据发送给与边缘服务器2，由边缘服务器2将该探针数据发送给客户端21。客户端21接收到探针数据后可以进行渲染，以及在渲染过程中根据接收到的探针数据，确定添加目标家具后的客厅场景中对象的着色效果；待渲染完成后，可以得到添加目标家具后的客厅图像并显示。
为了便于后续说明，以下对计算中心服务器生成探针数据的过程，以及客户端在渲染过程中，根据探针数据确定三维场景中对象的着色效果的过程进行介绍。
计算中心服务器生成探针数据的过程：
示例性地，计算中心服务器的渲染过程可以如下：将三维物体模型(可以包括人的模型或物的模型)加载到三维场景(也可以称为3D场景)中(这样可以将三维物体模型转换为三维场景中的对象)，接着，可以对三维场景中的对象进行渲染，以得到当前帧(也就是渲染后的图像)。为了模拟三维场景中光线进行多次反射后，三维场景中对象的着色效果，可以在对三维场景中的对象进行渲染过程中，在三维场景中放置多个探针，采用探针探测周围环境，以得到探针数据；然后，根据探针数据，确定三维场景中对象的着色效果。
图7b为示例性示出的三维场景中探针分布示意图。图7b中每一个小球，代表一个探针，在图7b的实施例中，探针为DDGI探针。
参照图7b，示例性地，每个探针在三维场景中放置的位置，以及每个探针与其他探针之间的位置关系可以按照需求设置，本申请实施例对此不作限制。例如，在图7b中，每个探针与其周围6个方向(正上方、正下方、正前方、正后方、正左方和正右方)上的6个探针之间的距离相等。此外，在三维场景中放置的探针的数量也可以按照需求设置，本申请实施例对此也不作限制。
其中，在三维场景中放置多个探针后，可以按照场景需求，为每个探针配置对应的属性数据(该属性数据用于渲染过程中)。其中，属性数据包括但不限于：探针的类型(如反射探针、DDGI探针)、探针的启用标识、探针的位置、探针的位置偏移(例如，按照预设的方式放置探针后，可以得到各个探针的初始位置；为了获取更好的着色效果，可以调整部分探针的位置；这样，针对这些探针而言，调整后的位置与初始位置的偏移，可以称为探针的位置偏移。例如，按照图1b的方式放置探针后，每个探针与其周围6个探针之间的距离均相等；若调整了某一个探针的位置，则该探针与其周围6个探针之间的距离不等)，等等；本申请对此不作限制。
示例性的，在三维场景中放置多个探针后，每个探针可以探测以其自身为中心的周围环境，即探测三维场景中以其自身为中心的周围对象的特性，并记录这些特性，作为该探针的环境数据。其中，周遭环境数据包括光照数据、颜色、可见性数据、材质、法向或纹理坐标中的至少一项。光照数据可以用于描述探针周围对象的出射光照，可见性数据，即各个角度的物体与这个探针的距离的分布数据，包括每个角度的距离的均值、距离的平方和距离的方差等数据。
示例性的，可以采用DDGI算法，生成每个探针对应的光照数据和可见性数据；以下以当前帧的一个探针为例，对生成该探针的光照数据和可见性数据的过程进行说明。首先，采样若干条从该探针发出的光线，以及计算这若干条光线与三维场景中各对象的第一个交点。接着，计算探针的若干条光线中每条光线与三维场景中各对象的第一个交点之间的距离，得到初始距离数据；以及计算三维场景中各对象与若干条光线中每条光线的第一个交点的光照，得到初始光照数据。随后，可以将初始距离数据从离散域，转换成连续域的球面数据，具体的，可以在球面上使用cos^k核函数(k为正整数)，对初始距离数据进行滤波处理，以得到候选距离数据。以及可以将初始距离数据的从离散域，转换成连续域的球面数据，类似地，可以在球面上使用cos^k核函数(k为正整数)，对初始距离数据的平方进行滤波处理，以得到候选距离数据的平方。以及可以将初始光照数据从离散域，转换成连续域的球面数据，具体的，可以在球面上使用cos^k核函数(k为正整数)，对初始光照数据进行滤波处理，以得到候选光照数据。然后，将该探针的候选距离数据，与上一帧的该探针的距离数据进行加权计算，得到当前帧的该探针的距离数据；将该探针的候选距离数据的平方，与上一帧的该探针的距离数据的平方进行加权计算，得到当前帧的该探针的距离数据的平方；以及将该探针的候选光照数据，与上一帧的该探针的光照数据进行加权计算，得到当前帧的该探针的光照数据。这样，可以得到当前帧的所有探针的光照数据和可见性数据。
示例性的，用于渲染过程的属性数据和环境数据，可以组成探针的探针数据。
示例性的，每个探针的光照数据和可见性数据，均可以采用二维图像表示，也可以采用球谐函数基底系数表示，还可以采用球面小波基底系数表示，本申请对此不作限制。
需要说明的是，假设三维场景中包括M(M为正整数)个探针，其中，M1个探针具有光照数据、可见性数据和属性数据中的任意一种数据，M2个探针具有光照数据、可见性数据和属性数据中的任意两种数据，M3个探针具有光照数据、可见性数据和属性数据，M4个探针不具有探针数据。其中，M1+M2+M3+M4＝M，M1、M2、M3和M1均为整数，M1、M2、M3和M4的数值，可以按照需求设置，本申请实施例对此不作限制。
客户端在渲染过程中，根据探针数据确定三维场景中对象的着色效果的过程：
示例性地，在客户端的渲染过程中，探针数据会被用于计算三维场景中对象的着色效果。具体来说，在渲染每个像素时，首先获取该像素对应的3D空间的坐标，然后查找包围该坐标的8个探针。接下来，通过探针的可见性数据计算每个探针对该像素的贡献权重，即通过距离判断探针与其3D坐标是否互相可见，若不可见，则权重为0，若可见，则再通过距离的平方计算探针的贡献权重。之后，使用贡献权重对探针的光照数据进行加权平均，得到该像素的着色结果。
由于探针数据的数据量比较大，计算中心服务器可以将探针数据压缩后再发送给客户端，以降低网络带宽。
图8a为示例性示出的编码框架示意图。
参照图8a，示例性地，编码器可以包括：码流负载均衡模块，数据形式转换模块、第一重排布模块和编码模块。
示例性地，码流负载均衡模块，可以用于确定探针数据的目标码率以及编码方式(如帧内编码或帧间编码)。
示例性的，数据形式转换模块，可以用于对环境数据进行数据形式转换，以将环境数据转换为更为紧凑的表示；或者增加渲染过程所需的重要性更高的数据在码流中占用的比特数。
示例性地，第一重排布模块，可以用于对探针的属性数据进行重排布。
其中，探针的属性数据可以包括用于数据形式转换的属性数据(后续称为第一属性数据)，和上述用于渲染过程中的属性数据(后续称为第二属性数据)。
示例性地，编码模块，用于编码，以得到码流。
需要说明的是，码流负载均衡模块、数据形式转换模块和第一重排布模块执行的步骤，属于编码器编码流程中的步骤。
应该理解的是，图8a仅是本申请实施例编码器的一个示例性，本申请实施例的编码器可以具有比图8a更少的模块。例如，编码器包括：码流负载均衡模块、数据形式转换模块以及编码模块；又例如，编码器包括：数据形式转换模块、第一重排布模块以及编码模块；还例如，编码器包括：数据形式转换模块和编码模块；等等。此外，本申请实施例的编码器可以具有比图8a更多的模块，本申请实施例对此不作限制。
应该理解的是，图8a中的码流负载均衡模块，数据形式转换模块、第一重排布模块和编码模块可以是相互独立的模块，或者其中的任意两个及两个以上的模块是一个整体，本申请实施例对此不作限制。此外，码流负载均衡模块，数据形式转换模块、第一重排布模块和编码模块是逻辑模块，编码器还可以划分为其他模块或者这些模块采用其他名称， 本申请实施例对此也不作限制。
应该理解的是，编码器仅包括编码模块，码流负载均衡模块、数据形式转换模块和第一重排布模块，可以独立于编码器，本申请实施例对此不作限制。本申请实施例以图8a中的编码器为例进行示例性说明。
图8b为示例性示出的数据形式转换模块结构示意图。
参照图8b，示例性地，数据形式转换模块可以包括：量化模块、域转换模块和第二重排布模块。
示例性地，量化模块，可以用于量化。
示例性地，域转换模块，可以用于域转换。
示例性地，域转换可以是指将数据的表示形式从一个域转换到另一个域。其中，域可以按照需求从不同角度进行划分，例如：
从是否归一化的角度划分，可以划分为：归一化域和非归一化域。
从色彩空间的角度划分，可以划分为：RGB域、YUV域、XYZ域和Lab域。
从数值变化曲线的角度划分，可以划分为：线性域和非线性域，其中，非线性域可以如指数域、PQ(Perceptual Quantization，感知量化)域、HLG(Hybird log gamma，混合对数伽马)域等。
从数值表示形式的角度划分，可以划分为：图像域和变换域。示例性的，图像域可以是指采用图像表示的域。示例性的，变换域可以是指使用基底函数与对应系数表示的域；对于变换基底域中的数据Y(t)，可以使用x个基底e_1(t)～e_x(t)对其进行近似，使得数据Y(t)近似等于x个变换基底与对应变换系数相乘的和。其中，变换基底包括但不限于：球谐函数基底、球面小波基底、特征向量等，本申请对此不作限制。
示例性地，第二重排布模块，可以用于进行数据的重排布。
应该理解的是，图8b仅是本申请实施例数据形式转换模块的一个示例性，本申请实施例的数据形式转换模块可以具有比图8b更少的模块，例如，数据形式转换模块仅包括域转换模块；又例如，数据形式转换模块仅包括量化模块和域转换模块；再例如，数据形式转换模块仅包括域转换模块和第二重排布模块，本申请实施例对此不作限制。此外，本申请实施例的数据形式转换模块可以具有比图8b更多的模块，本申请实施例对此也不作限制。
应该理解的是，图8b中的量化模块、域转换模块和第二重排布模块可以是相互独立的模块，或者其中的任意两个及两个以上的模块是一个整体，本申请实施例对此不作限制。此外，量化模块、域转换模块和第二重排布模块是逻辑模块，数据形式转换模块还可以划分为其他模块或者这些模块采用其他名称，本申请实施例对此也不作限制。
图9a为示例性示出的解码框架示意图。在图9a的实施例中，描述了与图8a中编码框架对应的解码框架。
参照图9a，示例性地，解码器可以包括：数据形式转换模块、第一重排布模块和解码模块。
示例性的，数据形式转换模块，可以用于对从码流中解码得到的部分数据进行数据形式转换，以得到探针数据。
示例性的，第一重排模块，可以用于对从码流中解码得到的另一部分数据进行重排布， 以得到探针的属性数据。其中，探针的属性数据可以包括用于数据形式转换的属性数据(后续称为第一属性数据)，和上述用于渲染过程中的属性数据(后续称为第二属性数据)。
示例性地，解码模块，用于对码流进行解码。
应该理解的是，解码器中的数据形式转换模块的数据形式转换过程，是编码器中的数据形式转换模块的数据形式转换过程的逆过程；以及解码器中的第一重排布模块的重排布过程，是编码器中的第一重排布模块的重排布过程的逆过程。
需要说明的是，数据形式转换模块和第一重排布模块执行的步骤，属于解码器解码流程中的步骤。
应该理解的是，图9a仅是本申请实施例解码器的一个示例性，本申请实施例的解码器可以具有比图9a更少的模块，例如，解码器包括数据形式转换模块和解码模块，本申请实施例对此不作限制。或者，本申请实施例的解码器可以具有比图9a示出的更多的模块，本申请实施例对此不作限制。
应该理解的是，图9a中的数据形式转换模块、第一重排布模块和解码模块可以是相互独立的模块，或者其中的任意两个及两个以上的模块是一个整体，本申请实施例对此不作限制。此外，数据形式转换模块、第一重排布模块和解码模块是逻辑模块，解码器还可以划分为其他模块或者这些模块采用其他名称，本申请实施例对此也不作限制。
应该理解的是，解码器仅包括解码模块，数据形式转换模块和第一重排布模块，可以独立于解码器，本申请实施例对此不作限制。本申请实施例以图9a中的解码器为例进行示例性说明。
图9b为示例性示出的数据形式转换模块结构示意图。
参照图9b，示例性地，数据形式转换模块可以包括：反量化模块、域转换模块和第二重排布模块。
示例性地，反量化模块，可以用于反量化。应该理解的是，解码器中反量化模块的反量化过程，是编码器中量化模块的量化过程的逆过程。
示例性地，域转换模块，可以用于域转换。应该理解的是，解码器中域转换模块的域转换过程，是编码器中域转换模块的域转换过程的逆过程。
示例性地，第二重排布模块，可以用于进行数据的重排布。应该理解的是，解码器中第二重排布模块的重排布过程，是编码器中第二重排布模块的重排布过程的逆过程。
应该理解的是，图9b仅是本申请实施例数据形式转换模块的一个示例性，本申请实施例的数据形式转换模块可以具有比图9b更少的模块。例如，数据形式转换模块仅包括反量化模块和域转换模块，或者，数据形式转换模块仅包括域转换模块和第二重排布模块，本申请实施例对此不作限制。或者，本申请实施例的数据形式转换模块可以具有比图9b更多的模块，本申请实施例对此不作限制。
应该理解的是，图9b中的反量化模块、域转换模块和第二重排布模块可以是相互独立的模块，或者其中的任意两个及两个以上的模块是一个整体，本申请实施例对此不作限制。此外，反量化模块、域转换模块和第二重排布模块是逻辑模块，数据形式转换模块还可以划分为其他模块或者这些模块采用其他名称，本申请实施例对此也不作限制。
请参考图10和图11，图10和图11为本申请实施例提供的编码方法的流程图。该编码方法可由上述解码器执行。编码方法描述为一系列的步骤或操作，应当理解的是，编码 方法可以以各种顺序执行和/或同时发生，不限于图10所示的执行顺序。如图10和图11所示，编码方法可以包括：
S1001、确定探针数据组的目标归一化组合。
其中，上述目标归一化组合为多个归一化组合中使上述探针数据组对应的渲染损失最小的归一化组合，上述目标归一化组合包括目标归一化方法和目标归一化参数。探针数据(probe data)组对应的渲染损失(rendering loss)，可以是探针数据组对应的渲染效果与探针数据组经过编解码后对应的渲染效果之间的误差。比如，上述渲染损失可以用PSNR进行度量，也可以用MSE或其他参数进行度量，本申请实施例对此不作限定。
探针数据组可以包括一帧或多帧中的单行探针的探针数据、一帧或多帧中的单个探针的探针数据、一帧或多帧中的单个通道探针的探针数据或一帧或多帧中的所有探针的探针数据。其中，探针数据与三维场景中的一个或多个探针对应，用于在渲染过程中确定所述三维场景中对象的着色效果，可以包括属性数据和周遭环境数据。探针数据中的周遭环境数据指的是每个探针处不同方向的属性数据，如光照数据、颜色、可见性数据、材质、法向、纹理坐标等信息。探针数据中的属性数据可以包括：探针的类型、探针是否启用、探针的位置、探针的相对初始位置的偏移、周遭环境数据在编码过程中所使用的参数等等，不一而足。
示例性地，云游戏场景中，计算中心服务器接收到客户端发送的视角切换指示后，可以采用云游戏场景中放置的多个探针探测周围环境以生成目标视角对应游戏场景的探针数据；然后将由探针数据构成的探针数据组发送给边缘服务器。由边缘服务器确定探针数据组的目标归一化组合。
又示例性地，室内装修场景中，计算中心服务器接收到客户端发送的添加家具指示后，可以采用室内装修场景中放置的多个探针探测周围环境以生成添加目标家具后的客厅场景对应的探针数据；然后将由探针数据构成的探针数据组发送给边缘服务器。由边缘服务器确定探针数据组的目标归一化组合。
如图12所示，在一种可能的实现方式中，可以先确定上述多个归一化组合中每个归一化组合对于上述探针数据组对应的渲染损失。然后将上述多个归一化组合中使上述探针数据组对应的渲染损失最小的归一化组合确定为上述目标归一化组合。
在一种可能的实现方式中，可以先根据上述每个归一化组合对上述探针数据组进行目标操作以得到上述每个归一化组合对于上述探针数据组的渲染结果。然后根据上述探针数据组经上述目标操作进行渲染得到的渲染结果和上述探针数据组未经上述目标操作进行渲染得到的渲染结果确定上述每个归一化组合对于上述探针数据组对应的渲染损失。其中，目标操作包括归一化、编解码和反归一化。
其中，上述编解码的具体方法可以采用本领域技术人员能够想到的任何一种方法进行处理，本申请实施例对此不作具体限定。例如，编解码的具体方法可以为HEVC、模拟编解码、低分辨率编解码、快速编解码等编解码方法。
可选地，上述多个归一化组合可以为由最小最大归一化方法和多个归一化参数组成的归一化组合。
M为最大归一化参数，m为最小归一化参数。
在一种可能的实现方式中，该方法还可以包括：根据上述参考目标归一化参数确定上述多个归一化组合中的归一化参数，上述参考目标归一化参数为与上述探针数据组相关的探针数据组的目标归一化参数。
例如，可以在参考目标归一化参数的1/(1+∈)倍至1+∈倍的范围以内选取多个数值作为上述多个归一化组合中的归一化参数。其中，∈的范围可以为0.01～0.05。
可选地，当前帧的探针数据组的目标归一化参数(如M和m)可以在上一帧的探针数据组的目标归一化参数的1/(1+∈)倍至1+∈倍的范围以内。
示例性地，假设当前帧的上一帧的探针数据组的目标归一化参数M为1，∈为0.01，则当前帧的探针数据组的目标归一化参数M的取值范围的下限为1/(1+0.01)*1≈0.99，当前帧的探针数据的目标归一化参数M的取值范围的上限为(1+0.01)*1＝1.01，即当前帧的探针数据的目标归一化参数M的取值范围为0.99～1.01。
可选地，上述多个归一化组合中的多个归一化参数可以为1。
S1002、根据上述目标归一化组合对上述探针数据组进行归一化以得到归一化探针数据组。
示例性地，云游戏场景中，计算中心服务器接收到客户端发送的视角切换指示后，可以采用云游戏场景中放置的多个探针探测周围环境以生成目标视角对应游戏场景的探针数据；然后将由探针数据构成的探针数据组发送给边缘服务器。由边缘服务器确定探针数据组的目标归一化组合，之后由根据该目标归一化组合对该探针数据组进行归一化以得到归一化探针数据组。
又示例性地，室内装修场景中，计算中心服务器接收到客户端发送的添加家具指示后，可以采用室内装修场景中放置的多个探针探测周围环境以生成添加目标家具后的客厅场景对应的探针数据；然后将由探针数据构成的探针数据组发送给边缘服务器。由边缘服务器确定探针数据组的目标归一化组合，之后由根据该目标归一化组合对该探针数据组进行归一化以得到归一化探针数据组。
其中，根据上述目标归一化组合对上述探针数据组进行归一化以得到归一化探针数据组可以采用本领域技术人员能够想到的任何一种方法进行处理。
例如，在上述目标归一化组合中的目标归一化方法为预设最大值归一化的情况下，使用预设最大值归一化和目标归一化参数对上述探针数据组进行归一化以得到归一化探针数据组。
又例如，在上述目标归一化组合中的目标归一化方法为最大最小归一化的情况下，使用最大最小归一化和目标归一化参数对上述探针数据组进行归一化以得到归一化探针数据组。
又例如，在上述目标归一化组合中的目标归一化方法为Z-Score归一化的情况下，使用0均值归一化和目标归一化参数对上述探针数据组进行归一化以得到归一化探针数据组。
S1003、将上述归一化探针数据组编入码流。
示例性地，云游戏场景中，边缘服务器可以在得到归一化的游戏场景的探针数据组后，可以将该数据组编入游戏场景的码流中。
又示例性地，室内装修场景中，边缘服务器可以在得到归一化的客厅场景对应的探针数据组后，可以将该数据组编入客厅场景的码流中。
在一种可能的实现方式中，还可以将上述目标归一化组合编入上述码流。
在一种可能的实现方式中，还可以根据上述探针数据组的目标归一化参数和参考目标归一化参数确定上述探针数据组的归一化参数变化量；将上述归一化参数变化量编入上述码流。其中，上述参考目标归一化参数为与上述探针数据组相关的探针数据组的目标归一化参数。
例如，在上述探针数据组为通过帧内编码方式编码的探针数据组的情况下，将上述目标归一化组合编入上述码流。
在一种可能的实现方式中，上述方法还可以包括：发送归一化信息，上述归一化信息用于指示目标归一化组合。
在一种可能的实现方式中，还可以根据上述探针数据组的目标归一化参数和参考目标归一化参数确定上述探针数据组的归一化参数变化量，将上述归一化参数变化量编入码流中。
示例性地，如图13所示，可以在所述探针数据组为通过帧内编码的探针数据组的情况下，将所述目标归一化组合编入所述码流，可以在所述探针数据组为通过帧间编码的探针数据组的情况下，将所述归一化参数变化量编入所述码流。其中帧内编码为编码当前帧时只使用了当前帧信息的编码方式，示例性的，可以使用HEVC的帧内编码来完成探针数据组的帧内编码；帧间编码为编码当前帧时使用了非当前帧信息的编码方式，示例性的，可以使用HEVC的帧间编码来完成探针数据组的帧间编码。
在一种可能的实现方式中，还可以根据上述探针数据组的目标归一化参数和参考目标归一化参数确定上述探针数据组的归一化参数变化量，上述参考目标归一化参数为与上述探针数据组相关的探针数据组的目标归一化参数；将第一信息编入上述码流中，上述第一信息用于指示上述探针数据组的目标归一化参数较上述参考目标归一化参数是否发生变化。
例如，可以在上述探针数据组为通过帧间编码方式编码的探针数据组的情况下，将第一信息编入上述码流中。
可选地，帧间编码方式可以为除帧内编码方式外的其他编码方式。
可选地，第一信息可以用不同的标记位指示上述探针数据组的目标归一化参数较上述参考目标归一化参数是否发生变化。
在一种可能的实现方式中，上述方法还可以包括：在上述第一信息指示上述探针数据组的目标归一化参数较上述参考目标归一化参数发生变化的情况下，将上述归一化参数变化量编入上述码流。
示例性地，如图14所示，可以在所述探针数据组为通过帧内编码的探针数据组的情况下，将所述目标归一化组合编入所述码流，可以在所述探针数据组为通过帧间编码的探针数据组的情况下，将目标归一化参数是否发生变化的标记编入码流，并在探针数据组的目标归一化参数较上述参考目标归一化参数发生变化的情况下，将上述归一化参数变化量编入上述码流。
在一种可能的实现方式中，还可以包括将索引信息编入上述码流。其中，上述索引信 息包括探针数据组的标识和上述探针数据组的归一化参数变化量。
可以看出，本申请实施例提供的编码方法在归一化过程中，不使用某种固定的归一化方法和归一化参数，而是从多个归一化方法和归一化参数的组合中，选取对探针数据对应的渲染损失最小的归一化方法和归一化参数的组合。相较于使用固定的归一化方法和归一化参数，使用使探针数据对应的渲染损失最小的归一化方法和归一化参数的组合进行归一化，能够减少压缩探针数据造成的渲染损失。
请参考图15和图16，图15和图16为本申请实施例提供的解码方法的流程图。该解码方法可由上述解码器执行。解码方法描述为一系列的步骤或操作，应当理解的是，解码方法可以以各种顺序执行和/或同时发生，不限于图15和图16所示的执行顺序。如图15和图16所示，解码方法可以包括：
S1501、解码码流以得到归一化探针数据组。
示例性地，云游戏场景中，客户端可以在获取到游戏场景的码流后，对该码流进行解码以得到归一化的游戏场景的探针数据组。
又示例性地，室内装修场景中，客户端可以在获取到客厅场景的码流后，对该码流进行解码以得到归一化的客厅场景对应的探针数据组。
S1502、根据探针数据组的目标归一化组合对上述归一化探针数据组进行反归一化以得到第二探针数据组。
上述目标归一化组合为多个归一化组合中使上述第一探针数据组对应的渲染损失最小的归一化组合，上述第一探针数据组为归一化前的上述归一化探针数据组，上述目标归一化组合包括目标归一化方法和目标归一化参数。
示例性地，云游戏场景中，客户端可以根据游戏场景的探针数据组的目标归一化组合，对归一化的游戏场景的探针数据组进行反归一化以得到游戏场景的探针数据组。
又示例性地，室内装修场景中，客户端可以根据客厅场景对应的探针数据组的目标归一化组合，对归一化的客厅场景对应的探针数据组进行反归一化以得到客厅场景对应的探针数据组。
在一种可能的实现方式中，还可以获取上述目标归一化组合。
在一种可能的实现方式中，可以通过获取归一化信息的方式获取上述目标归一化组合。其中，上述归一化信息用于指示目标归一化组合
在另一种可能的实现方式中，可以通过解码上述码流以得到上述目标归一化组合。
例如，在上述归一化探针数据组为通过帧内编码方式编码的探针数据组的情况下，可以通过解码上述码流以得到上述目标归一化组合。
在一种可能的实现方式中，还可以先解码上述码流以得到上述第一探针数据组的归一化参数变化量。然后根据上述归一化参数变化量和参考归一化组合确定上述目标归一化组合。其中，参考归一化组合为与上述第一探针数据组相关的探针数据组的目标归一化组合。
例如，可以在上述归一化探针数据组为通过帧间编码方式编码的探针数据组的情况下，根据上述第一探针数据组的目标归一化参数和参考目标归一化参数确定上述第一探针数据组的归一化参数变化量。
其中，判断一个探针数据组是否与当前探针数据组是相关的，可以通过多种度量方式进行度量，本申请实施例对此不作限定，其包括但不限于，计算两个探针数据组之间的皮 尔逊相关系数，如果皮尔逊相关系数大于第二预设阈值，则认为两组探针数据组中的一组与另一组是相关的；此外，也可以计算两个探针数据组之间的PSNR，如果PSNR大于预设阈值，则认为两组探针数据组中的一组与另一组是相关的。
在又一种可能的实现方式中，还可以先解码上述码流以得到第一信息，在上述第一信息指示上述第一探针数据组的目标归一化参数较上述参考目标归一化参数未发生变化的情况下，根据参考归一化组合确定上述目标归一化组合。其中，上述第一信息用于指示上述第一探针数据组的目标归一化参数较上述参考目标归一化参数是否发生变化，上述参考归一化组合为与上述第一探针数据组相关的探针数据组的目标归一化组合。
例如，可以在上述归一化探针数据组为通过帧间编码方式编码的探针数据组的情况下，先解码上述码流以得到第一信息，在上述第一信息指示上述第一探针数据组的目标归一化参数较上述参考目标归一化参数未发生变化的情况下，将参考归一化组合确定为上述目标归一化组合。
在又一种可能的实现方式中，还可以先解码上述码流以得到第一信息，在上述第一信息指示上述第一探针数据组的目标归一化参数较上述参考目标归一化参数发生变化的情况下，解码上述码流以得到上述第一探针数据组的归一化参数变化量并根据上述归一化参数变化量和上述参考归一化组合确定上述目标归一化组合。
例如，可以在上述归一化探针数据组为通过帧间编码方式编码的探针数据组的情况下，先解码上述码流以得到第一信息，在上述第一信息指示上述第一探针数据组的目标归一化参数较上述参考目标归一化参数未发生变化的情况下，解码上述码流以得到上述第一探针数据组的归一化参数变化量并根据上述归一化参数变化量和上述参考归一化组合确定上述目标归一化组合。
S1503、根据第二探针数据组进行渲染。
其中，根据第二探针数据组进行渲染的具体方法可以采用本领域技术人员能够想到的任何一种方法进行处理，本申请实施例对此不作具体限定。
示例性地，云游戏场景中，客户端可以根据游戏场景的探针数据组对游戏场景进行渲染。
又示例性地，室内装修场景中，客户端可以根据客厅场景对应的探针数据组对客厅场景进行渲染。
下面介绍用于执行上述解码方法的编码装置，如图8a所示，该编码装置可以包括：数据形式转换模块和编码模块。
数据形式转换模块，用于确定探针数据组的目标归一化组合。其中，上述目标归一化组合为多个归一化组合中使上述探针数据组对应的渲染损失最小的归一化组合，上述目标归一化组合包括目标归一化方法和目标归一化参数。
示例性地，数据形式转换模块可以用于执行上述编码方法中的S1001。
数据形式转换模块，还用于根据上述目标归一化组合对上述探针数据组进行归一化以得到归一化探针数据组。
示例性地，数据形式转换模块可以用于执行上述编码方法中的S1002。
编码模块，用于将上述归一化探针数据组编入码流。
示例性地，编码模块可以用于执行上述编码方法中的S1003。
在一种可能的实现方式中，上述数据形式转换模块具体用于：确定上述多个归一化组合中每个归一化组合对于上述探针数据组对应的渲染损失；将上述多个归一化组合中使上述探针数据组对应的渲染损失最小的归一化组合确定为上述目标归一化组合。
在一种可能的实现方式中，上述数据形式转换模块具体用于：根据上述每个归一化组合对上述探针数据组进行目标操作以得到上述每个归一化组合对于上述探针数据组的渲染结果，上述目标操作包括归一化、编解码和反归一化；根据上述探针数据组经上述目标操作进行渲染得到的渲染结果和上述探针数据组未经上述目标操作进行渲染得到的渲染结果确定上述每个归一化组合对于上述探针数据组对应的渲染损失。
在一种可能的实现方式中，上述编码模块还用于：将上述目标归一化组合编入上述码流。
在一种可能的实现方式中，上述数据形式转换模块还用于：根据上述探针数据组的目标归一化参数和参考目标归一化参数确定上述探针数据组的归一化参数变化量，上述参考目标归一化参数为与上述探针数据组相关的探针数据组的目标归一化参数；
在一种可能的实现方式中，上述编码模块，还用于将上述归一化参数变化量编入上述码流。
在一种可能的实现方式中，上述编码模块，还用于将第一信息编入上述码流中，上述第一信息用于指示上述探针数据组的目标归一化参数较上述参考目标归一化参数是否发生变化。
在一种可能的实现方式中，上述编码模块还用于：在上述第一信息指示上述探针数据组的目标归一化参数较上述参考目标归一化参数发生变化的情况下，将上述归一化参数变化量编入上述码流。
在一种可能的实现方式中，上述编码模块还用于：将索引信息编入上述码流，上述索引信息包括探针数据组的标识和上述探针数据组的归一化参数变化量。
在一种可能的实现方式中，上述数据形式转换模块还用于：根据上述参考目标归一化参数确定上述多个归一化组合中的归一化参数，上述参考目标归一化参数为与上述探针数据组相关的探针数据组的目标归一化参数。
在一种可能的实现方式中，上述探针数据组包括探针的周遭环境数据，上述周遭环境数据包括光照数据、颜色、可见性数据、材质、法向或纹理坐标中的至少一项。
下面介绍用于执行上述解码方法的解码装置。如图9a所示该解码装置可以包括：数据形式转换模块和数据形式转换模块。
解码模块，用于解码码流以得到归一化探针数据组。
示例性地，解码模块可以用于执行上述解码方法中的S1501。
数据形式转换模块，用于根据第一探针数据组的目标归一化组合对所述归一化探针数据组进行反归一化以得到第二探针数据组，所述目标归一化组合为多个归一化组合中对于所述第一探针数据组对应的渲染损失最小的归一化组合，所述第一探针数据组为归一化前的所述归一化探针数据组，所述目标归一化组合包括目标归一化方法和目标归一化参数。
示例性地，数据形式转换模块可以用于执行上述解码方法中的S1502。
数据形式转换模块，还用于根据上述第二探针数据组进行渲染。
示例性地，数据形式转换模块可以用于执行上述解码方法中的S1503。
在一种可能的实现方式中，上述解码模块还用于：获取上述目标归一化组合。
在一种可能的实现方式中，上述解码模块具体用于：解码上述码流以得到上述目标归一化组合。
在一种可能的实现方式中，上述解码模块具体用于：解码上述码流以得到上述第一探针数据组的归一化参数变化量；根据上述归一化参数变化量和参考归一化组合确定上述目标归一化组合，上述参考归一化组合为与上述第一探针数据组相关的探针数据组的目标归一化组合。
在一种可能的实现方式中，上述解码模块具体用于：解码上述码流以得到第一信息，上述第一信息用于指示上述第一探针数据组的目标归一化参数较上述参考目标归一化参数是否发生变化，上述参考目标归一化参数为与上述第一探针数据组相关的探针数据组的目标归一化参数；在上述第一信息指示上述第一探针数据组的目标归一化参数较上述参考目标归一化参数未发生变化的情况下，根据参考归一化组合确定上述目标归一化组合，上述参考归一化组合为与上述第一探针数据组相关的探针数据组的目标归一化组合；在所述第一信息指示所述第一探针数据组的目标归一化参数较所述参考目标归一化参数发生变化的情况下，解码所述码流以得到第二信息，所述第二信息用于指示所述第一探针数据组的归一化参数变化量并根据所述归一化参数变化量和所述参考归一化组合确定所述目标归一化组合。
本申请实施例还提供一种编码装置，该装置包括：至少一个处理器，当所述至少一个处理器执行程序代码或指令时，实现上述相关方法步骤实现上述实施例中的编码方法。
可选地，该装置还可以包括至少一个存储器，该至少一个存储器用于存储该程序代码或指令。
本申请实施例还提供一种解码装置，该装置包括：至少一个处理器，当所述至少一个处理器执行程序代码或指令时，实现上述相关方法步骤实现上述实施例中的解码方法。
可选地，该装置还可以包括至少一个存储器，该至少一个存储器用于存储该程序代码或指令。
本申请实施例还提供一种计算机存储介质，该计算机存储介质中存储有计算机指令，当该计算机指令在编码装置上运行时，使得编码装置执行上述相关方法步骤实现上述实施例中的编解码方法。
本申请实施例还提供了一种计算机程序产品，当该计算机程序产品在计算机上运行时，使得计算机执行上述相关步骤，以实现上述实施例中的编解码方法。
本申请实施例还提供一种编解码装置，这个装置具体可以是芯片、集成电路、组件或模块。具体的，该装置可包括相连的处理器和用于存储指令的存储器，或者该装置包括至少一个处理器，用于从外部存储器获取指令。当装置运行时，处理器可执行指令，以使芯片执行上述各方法实施例中的编解码方法。
图17示出了一种芯片1700的结构示意图。芯片1700包括一个或多个处理器1701以及接口电路1702。可选的，上述芯片1700还可以包含总线1703。
处理器1701可能是一种集成电路芯片，具有信号的处理能力。在实现过程中，上述编解码方法的各步骤可以通过处理器1701中的硬件的集成逻辑电路或者软件形式的指令完成。
可选地，上述的处理器1701可以是通用处理器、数字信号处理(digital signal proce ssing，DSP)器、集成电路(application specific integrated circuit，ASIC)、现场可编程门阵列(field-programmable gate array，FPGA)或者其他可编程逻辑器件、分立门或者晶体管逻辑器件、分立硬件组件。可以实现或者执行本申请实施例中的公开的各方法、步骤。通用处理器可以是微处理器或者该处理器也可以是任何常规的处理器等。
接口电路1702可以用于数据、指令或者信息的发送或者接收，处理器1701可以利用接口电路1702接收的数据、指令或者其他信息，进行加工，可以将加工完成信息通过接口电路1702发送出去。
可选的，芯片还包括存储器，存储器可以包括只读存储器和随机存取存储器，并向处理器提供操作指令和数据。存储器的一部分还可以包括非易失性随机存取存储器(non-vo latile random access memory，NVRAM)。
可选的，存储器存储了可执行软件模块或者数据结构，处理器可以通过调用存储器存储的操作指令(该操作指令可存储在操作***中)，执行相应的操作。
可选的，芯片可以使用在本申请实施例涉及的编码装置或DOP中。可选的，接口电路1702可用于输出处理器1701的执行结果。关于本申请实施例的一个或多个实施例提供的编解码方法可参考前述各个实施例，这里不再赘述。
需要说明的，处理器1701、接口电路1702各自对应的功能既可以通过硬件设计实现，也可以通过软件设计来实现，还可以通过软硬件结合的方式来实现，这里不作限制。
其中，本实施例提供的装置、计算机存储介质、计算机程序产品或芯片均用于执行上文所提供的对应的方法，因此，其所能达到的有益效果可参考上文所提供的对应的方法中的有益效果，此处不再赘述。
应理解，在本申请实施例的各种实施例中，上述各过程的序号的大小并不意味着执行顺序的先后，各过程的执行顺序应以其功能和内在逻辑确定，而不应对本申请实施例的实施过程构成任何限定。
本领域普通技术人员可以意识到，结合本文中所公开的实施例描述的各示例的单元及算法步骤，能够以电子硬件、或者计算机软件和电子硬件的结合来实现。这些功能究竟以硬件还是软件方式来执行，取决于技术方案的特定应用和设计约束条件。专业技术人员可以对每个特定的应用来使用不同方法来实现所描述的功能，但是这种实现不应认为超出本申请实施例的范围。
所属领域的技术人员可以清楚地了解到，为描述的方便和简洁，上述描述的***、装置和单元的具体工作过程，可以参考前述方法实施例中的对应过程，在此不再赘述。
在本申请实施例所提供的几个实施例中，应该理解到，所揭露的***、装置和方法，可以通过其他的方式实现。例如，以上所描述的装置实施例仅仅是示意性的，例如，上述单元的划分，仅仅为一种逻辑功能划分，实际实现时可以有另外的划分方式，例如多个单元或组件可以结合或者可以集成到另一个***，或一些特征可以忽略，或不执行。另一点，所显示或讨论的相互之间的耦合或直接耦合或通信连接可以是通过一些接口，装置或单元的间接耦合或通信连接，可以是电性，机械或其他的形式。
上述作为分离部件说明的单元可以是或者也可以不是物理上分开的，作为单元显示的部件可以是或者也可以不是物理单元，即可以位于一个地方，或者也可以分布到多个网络 单元上。可以根据实际的需要选择其中的部分或者全部单元来实现本实施例方案的目的。
另外，在本申请实施例各个实施例中的各功能单元可以集成在一个处理单元中，也可以是各个单元单独物理存在，也可以两个或两个以上单元集成在一个单元中。
上述功能如果以软件功能单元的形式实现并作为独立的产品销售或使用时，可以存储在一个计算机可读取存储介质中。基于这样的理解，本申请实施例的技术方案本质上或者说对现有技术做出贡献的部分或者该技术方案的部分可以以软件产品的形式体现出来，该计算机软件产品存储在一个存储介质中，包括若干指令用以使得一台计算机设备(可以是个人计算机，服务器，或者网络设备等)执行本申请实施例各个实施例上述方法的全部或部分步骤。而前述的存储介质包括：U盘、移动硬盘、只读存储器(Read Only Memory，ROM)、随机存取存储器(Random Access Memory，RAM)、磁碟或者光盘等各种可以存储程序代码的介质。
以上所述，仅为本申请实施例的具体实施方式，但本申请实施例的保护范围并不局限于此，任何熟悉本技术领域的技术人员在本申请实施例揭露的技术范围内，可轻易想到变化或替换，都应涵盖在本申请实施例的保护范围之内。因此，本申请实施例的保护范围应所述以权利要求的保护范围为准。

Claims (26)

  1. 一种编码方法，其特征在于，包括：
    确定探针数据组的目标归一化组合，所述目标归一化组合为多个归一化组合中使所述探针数据组对应的渲染损失最小的归一化组合，所述目标归一化组合包括目标归一化方法和目标归一化参数；
    根据所述目标归一化组合对所述探针数据组进行归一化以得到归一化探针数据组；
    将所述归一化探针数据组编入码流。
  2. 根据权利要求1所述的方法，其特征在于，所述确定探针数据组的目标归一化组合，包括：
    确定所述多个归一化组合中每个归一化组合对于所述探针数据组对应的渲染损失；
    将所述多个归一化组合中使所述探针数据组对应的渲染损失最小的归一化组合确定为所述目标归一化组合。
  3. 根据权利要求2所述的方法，其特征在于，所述确定所述多个归一化组合中每个归一化组合对于所述探针数据组对应的渲染损失，包括：
    根据所述每个归一化组合对所述探针数据组进行目标操作以得到所述每个归一化组合对于所述探针数据组的渲染结果，所述目标操作包括归一化、编解码和反归一化；
    根据所述探针数据组经所述目标操作进行渲染得到的渲染结果和所述探针数据组未经所述目标操作进行渲染得到的渲染结果确定所述每个归一化组合对于所述探针数据组对应的渲染损失。
  4. 根据权利要求1至3中任一项所述的方法，其特征在于，所述方法还包括：
    将所述目标归一化组合编入所述码流。
  5. 根据权利要求1至4中任一项所述的方法，其特征在于，所述方法还包括：
    根据所述探针数据组的目标归一化参数和参考目标归一化参数确定所述探针数据组的归一化参数变化量，所述参考目标归一化参数为与所述探针数据组相关的探针数据组的目标归一化参数；
    将所述归一化参数变化量编入所述码流。
  6. 根据权利要求1至4中任一项所述的方法，其特征在于，所述方法还包括：
    根据所述探针数据组的目标归一化参数和参考目标归一化参数确定所述探针数据组的归一化参数变化量，所述参考目标归一化参数为与所述探针数据组相关的探针数据组的目标归一化参数；
    将第一信息编入所述码流中，所述第一信息用于指示所述探针数据组的目标归一化参数较所述参考目标归一化参数是否发生变化。
  7. 根据权利要求6所述的方法，其特征在于，所述方法还包括：
    在所述第一信息指示所述探针数据组的目标归一化参数较所述参考目标归一化参数发生变化的情况下，将所述归一化参数变化量编入所述码流。
  8. 根据权利要求6或7所述的方法，其特征在于，所述方法还包括：
    将索引信息编入所述码流，所述索引信息包括所述探针数据组的标识和所述探针数据组的归一化参数变化量。
  9. 根据权利要求1至8中任一项所述的方法，其特征在于，所述方法还包括：
    根据参考目标归一化参数确定所述多个归一化组合中的归一化参数，所述参考目标归一化参数为与所述探针数据组相关的探针数据组的目标归一化参数。
  10. 根据权利要求1至9中任一项所述的方法，其特征在于，所述探针数据组包括探针的周遭环境数据，所述周遭环境数据包括光照数据、颜色、可见性数据、材质、法向或纹理坐标中的至少一项。
  11. 根据权利要求4所述的方法，其特征在于，所述将所述目标归一化组合编入所述码流，包括：
    在所述探针数据组为通过帧内编码的探针数据组的情况下，将所述目标归一化组合编入所述码流。
  12. 根据权利要求5所述的方法，其特征在于，所述将所述归一化参数变化量编入所述码流，包括：
    在所述探针数据组为通过帧间编码的探针数据组的情况下，将所述归一化参数变化量编入所述码流。
  13. 一种解码方法，其特征在于，包括：
    解码码流以得到归一化探针数据组；
    根据第一探针数据组的目标归一化组合对所述归一化探针数据组进行反归一化以得到第二探针数据组，所述目标归一化组合为多个归一化组合中使所述第一探针数据组对应的渲染损失最小的归一化组合，所述第一探针数据组为归一化前的所述归一化探针数据组，所述目标归一化组合包括目标归一化方法和目标归一化参数；
    根据所述第二探针数据组进行渲染。
  14. 根据权利要求13所述的方法，其特征在于，所述方法还包括：
    解码所述码流以得到所述第一探针数据组的归一化参数变化量；
    根据所述归一化参数变化量和参考归一化组合确定所述目标归一化组合，所述参考归一化组合为与所述第一探针数据组相关的探针数据组的目标归一化组合。
  15. 根据权利要求13所述的方法，其特征在于，所述方法还包括：
    解码所述码流以得到第一信息，所述第一信息用于指示所述第一探针数据组的目标归一化参数较所述参考目标归一化参数是否发生变化，所述参考目标归一化参数为与所述第一探针数据组相关的探针数据组的目标归一化参数；
    在所述第一信息指示所述第一探针数据组的目标归一化参数较所述参考目标归一化参数未发生变化的情况下，根据参考归一化组合确定所述目标归一化组合，所述参考归一化组合为与所述第一探针数据组相关的探针数据组的目标归一化组合；
    在所述第一信息指示所述第一探针数据组的目标归一化参数较所述参考目标归一化参数发生变化的情况下，解码所述码流以得到第二信息，所述第二信息用于指示所述第一探针数据组的归一化参数变化量并根据所述归一化参数变化量和所述参考归一化组合确定所述目标归一化组合。
  16. 一种编码装置，其特征在于，包括：数据形式转换模块和编码模块；
    所述数据形式转换模块，用于确定探针数据组的目标归一化组合并根据所述目标归一化组合对所述探针数据组进行归一化以得到归一化探针数据组，所述目标归一化组合为多 个归一化组合中使所述探针数据组对应的渲染损失最小的归一化组合，所述目标归一化组合包括目标归一化方法和目标归一化参数；
    所述编码模块，用于将所述归一化探针数据组编入码流。
  17. 根据权利要求16所述的装置，其特征在于，所述数据形式转换模块具体用于：
    确定所述多个归一化组合中每个归一化组合对于所述探针数据组对应的渲染损失；
    将所述多个归一化组合中使所述探针数据组对应的渲染损失最小的归一化组合确定为所述目标归一化组合。
  18. 根据权利要求17所述的装置，其特征在于，所述数据形式转换模块具体用于：
    根据所述每个归一化组合对所述探针数据组进行目标操作以得到所述每个归一化组合对于所述探针数据组的渲染结果，所述目标操作包括归一化、编解码和反归一化；
    根据所述探针数据组经所述目标操作进行渲染得到的渲染结果和所述探针数据组未经所述目标操作进行渲染得到的渲染结果确定所述每个归一化组合对于所述探针数据组对应的渲染损失。
  19. 根据权利要求16至18中任一项所述的装置，其特征在于，所述编码模块还用于：
    将所述目标归一化组合编入所述码流。
  20. 根据权利要求16至18中任一项所述的装置，其特征在于，所述数据形式转换模块还用于：
    根据所述探针数据组的目标归一化参数和参考目标归一化参数确定所述探针数据组的归一化参数变化量，所述参考目标归一化参数为与所述探针数据组相关的探针数据组的目标归一化参数；
    所述编码模块，还用于将所述归一化参数变化量编入所述码流。
  21. 一种解码装置，其特征在于，包括：解码模块和数据形式转换模块；
    所述解码模块，用于解码码流以得到归一化探针数据组；
    所述数据形式转换模块，用于根据第一探针数据组的目标归一化组合对所述归一化探针数据组进行反归一化以得到第二探针数据组，所述目标归一化组合为多个归一化组合中对于所述第一探针数据组对应的渲染损失最小的归一化组合，所述第一探针数据组为归一化前的所述归一化探针数据组，所述目标归一化组合包括目标归一化方法和目标归一化参数；
    所述数据形式转换模块，用于根据所述第二探针数据组进行渲染。
  22. 根据权利要求21所述的装置，其特征在于，所述解码模块具体用于：
    解码所述码流以得到所述第一探针数据组的归一化参数变化量；
    根据所述归一化参数变化量和参考归一化组合确定所述目标归一化组合，所述参考归一化组合为与所述第一探针数据组相关的探针数据组的目标归一化组合。
  23. [根据细则26改正 10.02.2023]
    一种编码装置，包括至少一个处理器和存储器，其特征在于，所述至少一个处理器执行存储在存储器中的程序或指令，以使得所述编码装置实现上述权利要求1至12中任一项所述的方法。
  24. 一种解码装置，包括至少一个处理器和存储器，其特征在于，所述至少一个处理器执行存储在存储器中的程序或指令，以使得所述解码装置实现上述权利要求13至15中任一项所述的方法。
  25. 一种计算机可读存储介质，用于存储计算机程序，其特征在于，当所述计算机程序在计算机或处理器运行时，使得所述计算机或所述处理器实现上述权利要求1至12中任一项或权利要求13至15中任一项所述的方法。
  26. 一种计算机程序产品，所述计算机程序产品中包含指令，其特征在于，当所述指令在计算机或处理器上运行时，使得所述计算机或所述处理器实现上述权利要求1至12中任一项或权利要求13至15中任一项所述的方法。
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