WO2013004161A1 - Method and device for classifying pixel of video image - Google Patents
Method and device for classifying pixel of video image Download PDFInfo
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- WO2013004161A1 WO2013004161A1 PCT/CN2012/078055 CN2012078055W WO2013004161A1 WO 2013004161 A1 WO2013004161 A1 WO 2013004161A1 CN 2012078055 W CN2012078055 W CN 2012078055W WO 2013004161 A1 WO2013004161 A1 WO 2013004161A1
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- 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
- H04N19/182—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 a pixel
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- 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
- H04N19/102—Methods or arrangements for coding, decoding, compressing or decompressing digital video signals using adaptive coding characterised by the element, parameter or selection affected or controlled by the adaptive coding
- H04N19/117—Filters, e.g. for pre-processing or post-processing
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- 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
- H04N19/134—Methods or arrangements for coding, decoding, compressing or decompressing digital video signals using adaptive coding characterised by the element, parameter or criterion affecting or controlling the adaptive coding
- H04N19/136—Incoming video signal characteristics or properties
- H04N19/14—Coding unit complexity, e.g. amount of activity or edge presence estimation
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- 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
- H04N19/176—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 block, e.g. a macroblock
Definitions
- the present invention relates to the field of digital signal processing technologies, and more particularly to a pixel classification method and apparatus for video images. Background technique
- the sender or receiver here can be a mobile phone, a digital phone terminal, a wireless device, a personal data assistant (PDA), a handheld or portable computer, a GPS receiver/navigator, a camera, an audio/video player, a video camera, a video recorder. , monitoring equipment, etc.
- PDA personal data assistant
- GPS receiver/navigator a GPS receiver/navigator
- camera an audio/video player
- video camera a video recorder.
- monitoring equipment etc.
- ALF Adaptive Loop Filter
- HEVC Adaptive Loop Filter
- ALF is applied to the reconstructed image deblocking filtered output image.
- HEVC defines a pixel classification method based on the local statistical characteristics of pixels. This classification method divides all the pixels in the image into 16 categories, and uses the pixels in each category to train the ALF coefficients for the pixels.
- the ALF coefficient and the pixel class are combined, the filter coefficients are retrained for the merged class, and finally the number of filters and corresponding coefficients that need to be written into the code stream are obtained at the encoding end, And use these filter coefficients to filter the image.
- three kinds of diamond filter structures are designed in HEVC, as shown in Figure 1. 5x5, 7x7 and 9x7.
- the ALF coefficient can utilize the statistical characteristics of the local direction and variance of the image in the existing HEVC, calculate the direction value and the variance value of the pixel block, and obtain the pixel according to the direction value and the variance value.
- the classification result of the block where the direction value contains 3 values, and the variance value contains 5 values.
- the pixel classification method includes:
- Step 201 Calculate the horizontal activity vertical activity and the vertical activity horizontal activity of each 4x4 pixel block,
- i represents the relative vertical coordinate of the pixel
- j represents the relative horizontal coordinate of the pixel
- sum represents the summation operation
- R represents the pixel
- Step 203 Quantify the sum of the horizontal activity and the vertical activity of the 4x4 pixel block into 5 values as the variance value of the pixel block:
- A Q (Horizontal activity + Vertical activity), Q ( - ) is a quantization function
- Step 204 Obtain a classification result of the pixel block according to the direction value and the variance value of the pixel block.
- This classification method utilizes the gradient of the local part of the pixel to represent the directional characteristic, and the local variance represents the texture intensity feature, although the different categories are distinguished to some extent.
- the pixels, but taking into account the main characteristics of the filter contain two parameters of bandwidth and direction, where the bandwidth reflects the strength of the airspace edge.
- the directional characteristics tend to have a more pronounced effect on the filter.
- the horizontal and vertical directions are used to distinguish the internal texture direction of the image, and the image characteristics are obviously not satisfied. Summary of the invention
- An object of the embodiments of the present invention is to provide a pixel classification and apparatus for video images, so as to improve the rationality of the pixel class arrangement method and improve the coding efficiency.
- a pixel classification method for a video image including: obtaining a direction value corresponding to any pixel or a pixel block in a video image;
- a pixel classification apparatus for a video image including: a direction obtaining unit, configured to obtain a direction value corresponding to any pixel or a pixel block in a video image; a complexity obtaining unit, configured to Obtaining a complexity value corresponding to the pixel or the pixel block; wherein, the number of classifications of the direction value is greater than or equal to the number of classifications of the complexity value;
- a classification unit configured to obtain a classification result of the pixel according to the direction value and the complexity value of the pixel.
- the invention improves the proportion of the directional characteristic classification in the process of classifying the adaptively filtered pixels or pixel blocks, that is, the number of classifications of the direction values is greater than or equal to the number of classifications of the complexity values, thereby improving the rationality of the filter design. Finally, the coding efficiency is improved.
- FIG. 1 is a schematic structural view of a filter in the prior art
- FIG. 2 is a schematic flow chart of a pixel classification method in the prior art
- FIG. 3 is a schematic flowchart diagram of an embodiment of a pixel classification method according to the present invention.
- FIG. 4 is a schematic flowchart diagram of another embodiment of a pixel classification method according to the present invention
- FIG. 5 is a schematic flowchart diagram of another embodiment of a pixel classification method according to the present invention
- FIG. 6 is a schematic structural diagram of an embodiment of a pixel classification apparatus according to the present invention
- FIG. 7 is a schematic structural diagram of another embodiment of a pixel sorting apparatus according to the present invention.
- FIG. 8 is a schematic structural diagram of another embodiment of a pixel sorting apparatus according to the present invention. Detailed ways
- video codecs are widely used in various electronic devices, such as: mobile phones, wireless devices, personal data assistants (PDAs), handheld or portable computers, GPS receivers/navigators, cameras, audio/ Video player, video camera, video recorder, monitoring equipment, etc.
- PDAs personal data assistants
- video encoder or video decoder can be directly implemented by a digital circuit or a chip such as a DSP (digital signal processor), or can be executed by a software code to execute the software in the processor. The process is implemented.
- DSP digital signal processor
- the embodiment of the invention proposes a new pixel classification method, which not only considers the important influence of the pixel directional characteristic on the filter coefficient training, but also considers the influence of the local variance of the region where the pixel is located on the filter strength. In order to facilitate the combination of coefficients, a reasonable arrangement of pixel categories is designed, and finally the coding efficiency is improved.
- the directionality uses the gradient to calculate the direction and intensity of the local texture of the image, and the number of classifications of the direction values is greater than or equal to the number of classifications of the complexity values.
- an embodiment of a pixel classification method for a video image provided by the present invention is used to obtain a classification of any pixel or pixel block in a video image, including:
- the pixel classification method can implement classification of one pixel or classification in units of pixel blocks.
- the direction value corresponding to the pixel or pixel block is calculated using four gradient values. a step of this step
- the methods include:
- the four gradient values are calculated by the following formula, grad_h ⁇ i,j) X(i + k, j + l- 1)
- grad—h(i,j), grad—v(i,j), grad—d ⁇ ) and grad—u ⁇ ) respectively represent (horizontal horizontal gradient, vertical gradient, 45° angular gradient, and 135° angular gradient) 4 gradient values, where X represents a pixel, i represents the vertical coordinate of the current pixel, j represents the horizontal coordinate of the current pixel, K represents the offset value of the current pixel vertical coordinate, and 1 represents the offset value of the current pixel horizontal coordinate.
- an integer value of 4 values between 0 and 3 or an integer of 5 directions between 0 and 4 can be obtained from the four gradient values.
- S302 Obtain a complexity value corresponding to the pixel or the pixel block, where the number of classifications of the direction value is greater than or equal to the number of classifications of the complexity value;
- One embodiment of the step includes processing a gradient sum of the horizontal gradient value and the vertical gradient value using a quantization function to obtain a complexity value corresponding to the pixel or pixel block.
- Complexity values include: 0, 1, 2, 3 or 0, 1, 2.
- S303 Obtain a classification result of the pixel or the pixel block according to the direction value and the complexity value of the pixel or the pixel block.
- the above method may be performed in the encoder or in the decoder.
- the method further comprises: filtering the pixel or the pixel block by using the adaptive loop filter corresponding to the classification result.
- FIG. 4 another embodiment of a pixel classification method for a video image provided by the present invention includes:
- S401 Calculate four gradient values corresponding to the pixel or the pixel block for any pixel or pixel block in the encoded image: horizontal gradient value, vertical gradient value, 45° angular gradient value, and 135° angular gradient value;
- grad— h ⁇ ), grad_v(y′), grad—d ⁇ ) and grad— u ⁇ ) represent the horizontal gradient of the ( ⁇ ) position, the vertical gradient, the 45° angular gradient and the 135° angular gradient, respectively.
- X represents a pixel
- i represents the vertical coordinate of the current pixel
- j represents the horizontal coordinate of the current pixel
- K represents the offset value of the current pixel vertical coordinate
- 1 represents the offset value of the current pixel horizontal coordinate.
- S402 Obtain a direction value corresponding to the pixel or the pixel block according to the four gradient values. Specifically, select a direction value corresponding to a minimum value of the four gradient values as a direction value of the pixel or the pixel block.
- S403 processing, by using a quantization function, a gradient sum of the horizontal gradient value and the vertical gradient value to obtain a complexity value corresponding to the pixel or the pixel block;
- S404 Obtain a classification result of the pixel or the pixel block according to the direction value and the complexity value of the pixel or the pixel block.
- the foregoing method may be implemented on the decoding end and may also be implemented on the encoding end. Further, if the method is implemented on the decoding end, the method further includes the following steps:
- S405 Filter the pixel or the pixel block by using an ALF filter corresponding to the classification result.
- ALF needs to pass some self-information compression coding to the decoding end. After receiving the code stream, the decoding end first needs to decode the information to obtain the ALF syntax element. And filtering the pixel or the pixel block by using the ALF filter corresponding to the classification result.
- the direction value of the pixel or the pixel block is obtained according to the four gradient values, the direction value includes 4 values, the complexity value includes 4 values, and the arrangement method of 16 pixel categories is obtained, and the texture directivity classification is greater than or equal to the texture.
- Complexity classification this classification method can fully exploit the characteristics of pixels or pixel blocks, which is beneficial to the final merge operation of the filter, and finally achieves the improvement of coding efficiency.
- FIG. 5 another embodiment of a pixel classification method for a video image provided by the present invention includes:
- S501 Calculate four gradient values corresponding to the pixel or the pixel block for any pixel or pixel block in the encoded image: horizontal gradient value, vertical gradient value, 45° angular gradient value, and 135° angular gradient value;
- grad— h ⁇ ), grad_v(y′), grad—d ⁇ ) and grad— u ⁇ ) represent the horizontal gradient of the ( ⁇ ) position, the vertical gradient, the 45° angular gradient and the 135° angular gradient, respectively.
- S502 Obtain a direction value corresponding to the pixel or the pixel block according to the four gradient values. If the absolute value of the difference between the maximum value and the minimum value of the four gradient values is less than a threshold value, the direction value is the first direction. Value; otherwise, the direction value corresponding to the minimum of the four gradient values is selected as the direction value of the pixel or the pixel block;
- the direction value D 0;
- S503 processing, by using a quantization function, a gradient sum of the horizontal gradient value and the vertical gradient value to obtain a complexity value corresponding to the pixel or the pixel block;
- the foregoing method may be implemented on the decoding end and may also be implemented on the encoding end. Further, if the method is implemented on the decoding end, the method further includes the following steps:
- S505 Filter the pixel or the pixel block by using an ALF filter corresponding to the classification result.
- ALF needs to pass some self-information compression coding to the decoding end. After receiving the code stream, the decoding end first needs to decode the information to obtain the ALF syntax element. And filtering the pixel or the pixel block by using the ALF filter corresponding to the classification result.
- the direction value of the pixel or the pixel block is obtained according to the four gradient values, the direction value includes five values, the complexity value includes three values, and the arrangement method of the 15 pixel categories is obtained, and the texture directivity classification is greater than or equal to the texture.
- Complexity classification this classification method can fully exploit the characteristics of pixels or pixel blocks, which is beneficial to the final merge operation of the filter, and finally achieves the improvement of coding efficiency.
- a person skilled in the art can understand that all or part of the process of implementing the above embodiment method can be completed by a computer program to instruct related hardware, and the program can be stored in a computer readable storage medium, the program When executed, the flow of an embodiment of the methods as described above may be included.
- the storage medium may be a magnetic disk, an optical disk, a read-only memory (ROM), or a random access memory (RAM).
- the present invention also provides a pixel classification apparatus for a video image, which may be located in an encoder or a decoder.
- the pixel classifying device of the video image may be implemented by a hardware circuit or by software in cooperation with hardware.
- a pixel classification device that calls a video image by a processor implements classification of pixels.
- the pixel classifying device of the video image can perform various methods and processes in the above method embodiments.
- an embodiment of a pixel classification apparatus for a video image according to the present invention includes: a direction obtaining unit 701, configured to obtain a direction value corresponding to any pixel or a pixel block in a video image;
- the complexity obtaining unit 702 is configured to obtain a complexity value corresponding to the pixel or the pixel block, where the number of classifications of the direction value is greater than or equal to the number of classifications of the complexity value;
- an embodiment of a pixel classifying apparatus for a video image according to the present invention includes: a gradient value calculating unit 801, configured to calculate four gradient values corresponding to the pixel or the pixel block: a horizontal gradient value, a vertical gradient value, and 45 Q angle gradient value and 135° angle gradient value;
- the obtaining unit 802 is configured to obtain, according to the four gradient values, a direction value corresponding to the pixel or the pixel block;
- a complexity obtaining unit 803 configured to process a gradient sum of the horizontal gradient value and the vertical gradient value by using a quantization function, to obtain a complexity value corresponding to the pixel or the pixel block; wherein, the number of classifications of the direction value is greater than or equal to the complexity The number of categories of values;
- the classifying unit 804 is configured to obtain a classification result of the pixel according to the direction value and the complexity value of the pixel.
- the complexity obtaining unit 803 selects a direction value corresponding to a minimum value among the four gradient values as a direction value of the pixel or the pixel block.
- the complexity values include: 0, 1 , 2, 3.
- the classification result C A + 4 * D; where A is the complexity value of the pixel and D is the direction value of the pixel.
- the complexity obtaining unit 803 determines that the direction value corresponding to the pixel or the pixel block is the first direction value. Otherwise, the complexity obtaining unit selects a direction value corresponding to a minimum value among the four gradient values as a direction value of the pixel, wherein the first direction value is a value different from a direction value corresponding to the four gradient values.
- the corresponding direction value D 4; complexity values include: 0, 1 , 2.
- Classification result eight + 3 * 0; where A is the complexity value of the pixel and D is the direction value of the pixel.
- the pixel classification device of the above video image may be implemented in an encoder or may be implemented in a decoder.
- the method further includes: And a filtering module, configured to filter the pixel or the pixel block by using an adaptive loop filter corresponding to the classification result.
- the above embodiment not only considers the important influence of the pixel directivity feature on the filter coefficient training, but also considers the influence of the local variance of the pixel region on the filter strength.
- the number of the direction value is greater than or equal to the number of the complexity value. A reasonable arrangement of pixel categories is used to achieve an improvement in coding efficiency.
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Abstract
Disclosed are a method and device for classifying a pixel of a video image. An embodiment of the method comprises: acquiring a directional value corresponding to any pixel or pixel block in the video image; acquiring a complexity value corresponding to the pixel or pixel block; where the classification number of the directional value is greater than or equal to the classification number of the complexity value; and acquiring a classification result of the pixel on the basis of the directional value and of the complexity value of the pixel. Embodiments of the present invention increase the proportion of a directional characteristic classification in the process of classifying the pixel or pixel block of adaptive filtering, thus improving the rationality of a filter design, and allowing for improved coding efficiency.
Description
一种视频图像的像素分类方法和装置 Method and device for pixel classification of video images
本申请要求于 2011 年 07 月 01 日提交中国专利局、 申请号为 201110184115.7、 发明名称为 "一种视频图像的像素分类方法和装置" 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 The present application claims priority to Chinese Patent Application No. 201110184115.7, entitled "Pixel Classification Method and Apparatus for Video Image", filed on July 1, 2011, the entire contents of which are incorporated by reference. In this application. Technical field
本发明涉及数字信号处理技术领域,尤其是一种视频图像的像素分类方法 和装置。 背景技术 The present invention relates to the field of digital signal processing technologies, and more particularly to a pixel classification method and apparatus for video images. Background technique
在数字通信领域, 语音、 图像、 音频、 视频的传输有着非常广泛的应用需 求, 如手机通话、 音视频会议、 广播电视、 多媒体娱乐等。 随着网络技术的发 展, 影视点播、 网络电视、 可视电话等已成为宽带网络的主要业务, 并且这些 业务也将成为第三代(3G, the 3rd Generation )无线网络的主要业务。 为了降 低视频信号存储或者传输过程中占用的资源,视频信号在发送端进行压缩处理 后传输到接收端,接收端通过解压缩处理恢复视频信号并进行播放。这里的发 送端或者接收端可以是移动电话, 数字电话终端, 无线装置, 个人数据助理 ( PDA ), 手持式或便携式计算机, GPS接收机 /导航器, 照相机, 音频 /视频播 放器, 摄像机, 录像机, 监控设备等。 In the field of digital communications, voice, image, audio, and video transmissions have a wide range of application requirements, such as mobile phone calls, audio and video conferencing, broadcast television, multimedia entertainment, and the like. With the development of network technology, video on demand, Internet TV, videophone, etc. have become the main business of broadband networks, and these services will become the main business of the 3rd generation (3G, the 3rd Generation) wireless network. In order to reduce the resources occupied during video signal storage or transmission, the video signal is compressed at the transmitting end and transmitted to the receiving end, and the receiving end recovers the video signal and plays it by decompressing. The sender or receiver here can be a mobile phone, a digital phone terminal, a wireless device, a personal data assistant (PDA), a handheld or portable computer, a GPS receiver/navigator, a camera, an audio/video player, a video camera, a video recorder. , monitoring equipment, etc.
ALF ( Adaptive Loop Filter, 自适应环路滤波)技术是指利用解码重构图 像和原始输入图像训练多组滤波器系数,对编码重构图像进行滤波,提高重构 图像质量, 同时在编码环路内部通过提高运动补偿预测性能, 进而提高编码效 率。 在最新的编码标准 HEVC中, ALF应用在重构图像去块效应滤波后的输出 图像上。 首先, HEVC根据像素局部统计特性定义了像素分类方法, 用该分类 方法将图像中的全部像素分为 16种类别,利用每种类别中的像素训练用于该类 像素的 ALF系数。 接着, 根据编码的率失真最优准则, 对 ALF系数和像素类别 进行合并, 对合并后的类别重新训练滤波器系数, 最终在编码端得到需要写入 码流的滤波器数目和对应的系数, 并用这些滤波器系数对图像进行滤波处理。 为了得到较好的滤波性能, HEVC中设计了 3种菱形的滤波器结构, 如图 1所示
5x5,7x7 和 9x7。 ALF (Adaptive Loop Filter) technology is to train multiple reconstructed images and original input images to train multiple sets of filter coefficients, filter the reconstructed images, improve the reconstructed image quality, and simultaneously encode loops. The internal performance is improved by improving motion compensation prediction performance. In the latest coding standard HEVC, ALF is applied to the reconstructed image deblocking filtered output image. First, HEVC defines a pixel classification method based on the local statistical characteristics of pixels. This classification method divides all the pixels in the image into 16 categories, and uses the pixels in each category to train the ALF coefficients for the pixels. Then, according to the coded rate distortion optimal criterion, the ALF coefficient and the pixel class are combined, the filter coefficients are retrained for the merged class, and finally the number of filters and corresponding coefficients that need to be written into the code stream are obtained at the encoding end, And use these filter coefficients to filter the image. In order to obtain better filtering performance, three kinds of diamond filter structures are designed in HEVC, as shown in Figure 1. 5x5, 7x7 and 9x7.
为了^ ALF系数能够更好的去除压缩噪声, 在现有的 HEVC中利用了图像 局部方向和方差的统计特性,计算像素块的方向值和方差值, 并根据方向值和 方差值获得像素块的分类结果, 其中方向值包含 3个值, 方差值包含 5个值。 以 4x4像素块为例, 参考图 2, 像素分类方法包括: In order to better remove the compression noise, the ALF coefficient can utilize the statistical characteristics of the local direction and variance of the image in the existing HEVC, calculate the direction value and the variance value of the pixel block, and obtain the pixel according to the direction value and the variance value. The classification result of the block, where the direction value contains 3 values, and the variance value contains 5 values. Taking a 4x4 pixel block as an example, referring to FIG. 2, the pixel classification method includes:
步骤 201 : 计算每个 4x4像素块的水平活动性 Vertical activity和垂直活动性 Horizontal activity, Step 201: Calculate the horizontal activity vertical activity and the vertical activity horizontal activity of each 4x4 pixel block,
Vertical activity = sunii d | (R(i,j )« 1 )-R(i- 1 ,j )-R(i+ 1 ,j ) | i,j =0...3 Vertical activity = sunii d | (R(i,j )« 1 )-R(i- 1 ,j )-R(i+ 1 ,j ) | i,j =0...3
Horizontal activity = sumij|(R(i,j)«l)-R(i,j-l)-R(i,j+l)| i,j=0...3 Horizontal activity = sumij|(R(i,j)«l)-R(i,j-l)-R(i,j+l)| i,j=0...3
其中, i表示像素的相对垂直坐标, j表示像素的相对水平坐标; sum表示 求和运算; R表示像素 Where i represents the relative vertical coordinate of the pixel, j represents the relative horizontal coordinate of the pixel; sum represents the summation operation; R represents the pixel
步骤 202: 根据像素块的水平活动性和垂直活动性, 获得像素块的方向值; ^口果 Vertical activity > threshold*Horizontal activity, ^ -么定义方向值 D = 1; ^口果 Horizontal activity > threshold* Vertical activity, ^^么定义方向值 D = 2; Step 202: Obtain a direction value of the pixel block according to the horizontal activity and vertical activity of the pixel block; ^Vertical activity > threshold*Horizontal activity, ^ - define the direction value D = 1; ^口果Horizontal activity > threshold * Vertical activity, ^^ defines the direction value D = 2;
其余情况, 方向值 D = 0。 In the remaining cases, the direction value D = 0.
步骤 203 : 将该 4x4像素块水平活动性和垂直活动性之和量化为 5个值, 作 为该像素块的方差值: Step 203: Quantify the sum of the horizontal activity and the vertical activity of the 4x4 pixel block into 5 values as the variance value of the pixel block:
A = Q (Horizontal activity + Vertical activity), Q ( - )为量化函数 A = Q (Horizontal activity + Vertical activity), Q ( - ) is a quantization function
步骤 204: 根据该像素块的方向值和方差值, 获得该像素块的分类结果。 当前 4x4像素块的类别 C可以记作: C = A + 5 * D; 其中 A为像素的梯度和, D为该像素的方向值。 Step 204: Obtain a classification result of the pixel block according to the direction value and the variance value of the pixel block. The category C of the current 4x4 pixel block can be written as: C = A + 5 * D; where A is the gradient of the pixel and D is the direction value of the pixel.
发明人在实现本发明的过程中, 发现现有技术至少存在以下缺点: 这种分类方法利用了像素局部的梯度表示方向性特征,利用局部方差表示 纹理强度特征, 虽然一定程度上区分了不同类别的像素,但是考虑到滤波器的 主要特征包含带宽和方向两个参数, 其中带宽反应了空域边缘的强度。 然而, 方向性特征往往对滤波器的影响更加明显 ,仅仅利用水平和垂直两个方向来区 分图像内部纹理方向, 显然不能满足图像特性。
发明内容 In the process of implementing the present invention, the inventors have found that the prior art has at least the following disadvantages: This classification method utilizes the gradient of the local part of the pixel to represent the directional characteristic, and the local variance represents the texture intensity feature, although the different categories are distinguished to some extent. The pixels, but taking into account the main characteristics of the filter contain two parameters of bandwidth and direction, where the bandwidth reflects the strength of the airspace edge. However, the directional characteristics tend to have a more pronounced effect on the filter. The horizontal and vertical directions are used to distinguish the internal texture direction of the image, and the image characteristics are obviously not satisfied. Summary of the invention
本发明实施例的目的在于提供一种视频图像的像素分类和装置,以提高像 素类别排列方法的合理性, 实现编码效率的提升。 根据本发明的一实施例, 提供一种视频图像的像素分类方法, 包括: 获得视频图像中的任一像素或像素块对应的方向值; An object of the embodiments of the present invention is to provide a pixel classification and apparatus for video images, so as to improve the rationality of the pixel class arrangement method and improve the coding efficiency. According to an embodiment of the present invention, a pixel classification method for a video image is provided, including: obtaining a direction value corresponding to any pixel or a pixel block in a video image;
获得所述像素或像素块对应的复杂度值; 其中, 方向值的分类数量大于或 等于复杂度值的分类数量; Obtaining a complexity value corresponding to the pixel or the pixel block; wherein, the number of classifications of the direction value is greater than or equal to the number of classifications of the complexity value;
根据该像素的方向值和复杂度值, 获得该像素的分类结果。 根据本发明的另一实施例, 提供一种视频图像的像素分类装置, 包括: 方向获得单元, 用于获得视频图像中的任一像素或像素块对应的方向值; 复杂度获得单元, 用于获得所述像素或像素块对应的复杂度值; 其中, 方 向值的分类数量大于或等于复杂度值的分类数量; The classification result of the pixel is obtained according to the direction value and the complexity value of the pixel. According to another embodiment of the present invention, a pixel classification apparatus for a video image is provided, including: a direction obtaining unit, configured to obtain a direction value corresponding to any pixel or a pixel block in a video image; a complexity obtaining unit, configured to Obtaining a complexity value corresponding to the pixel or the pixel block; wherein, the number of classifications of the direction value is greater than or equal to the number of classifications of the complexity value;
分类单元,用于根据该像素的方向值和复杂度值,获得该像素的分类结果。 本发明通过在自适应滤波的像素或者像素块进行分类的过程中提升方向 特性分类的比重, 也就是方向值的分类数量大于或等于复杂度值的分类数量, 提升了滤波器设计的合理性, 最终实现编码效率的提升。 附图说明 And a classification unit, configured to obtain a classification result of the pixel according to the direction value and the complexity value of the pixel. The invention improves the proportion of the directional characteristic classification in the process of classifying the adaptively filtered pixels or pixel blocks, that is, the number of classifications of the direction values is greater than or equal to the number of classifications of the complexity values, thereby improving the rationality of the filter design. Finally, the coding efficiency is improved. DRAWINGS
为了更清楚地说明本发明实施例或现有技术中的技术方案,下面将对实施 例或现有技术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 中的附图仅仅是本发明的一些实施例,对于本领域普通技术人员来讲,在不付 出创造性劳动性的前提下, 还可以根据这些附图获得其他的附图。 In order to more clearly illustrate the embodiments of the present invention or the technical solutions in the prior art, the drawings used in the embodiments or the description of the prior art will be briefly described below. Obviously, the drawings in the following description are only It is a certain embodiment of the present invention, and other drawings can be obtained from those skilled in the art without any inventive labor.
图 1为现有技术中滤波器结构示意图; 1 is a schematic structural view of a filter in the prior art;
图 2为现有技术中一种像素分类方法的流程示意图; 2 is a schematic flow chart of a pixel classification method in the prior art;
图 3为本发明提供的像素分类方法一个实施例的流程示意图; FIG. 3 is a schematic flowchart diagram of an embodiment of a pixel classification method according to the present invention; FIG.
图 4为本发明提供的像素分类方法另一个实施例的流程示意图;
图 5为本发明提供的像素分类方法另一个实施例的流程示意图; 图 6为本发明提供的像素分类装置一个实施例的结构示意图; FIG. 4 is a schematic flowchart diagram of another embodiment of a pixel classification method according to the present invention; FIG. FIG. 5 is a schematic flowchart diagram of another embodiment of a pixel classification method according to the present invention; FIG. 6 is a schematic structural diagram of an embodiment of a pixel classification apparatus according to the present invention;
图 7为本发明提供的像素分类装置另一个实施例的结构示意图; FIG. 7 is a schematic structural diagram of another embodiment of a pixel sorting apparatus according to the present invention; FIG.
图 8为本发明提供的像素分类装置另一个实施例的结构示意图。 具体实施方式 FIG. 8 is a schematic structural diagram of another embodiment of a pixel sorting apparatus according to the present invention. Detailed ways
下面将结合本发明实施例中的附图,对本发明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发明一部分实施例, 而不是 全部的实施例。基于本发明中的实施例, 本领域普通技术人员在没有作出创造 性劳动前提下所获得的所有其他实施例, 都属于本发明保护的范围。 BRIEF DESCRIPTION OF THE DRAWINGS The technical solutions in the embodiments of the present invention will be described in detail below with reference to the accompanying drawings. All other embodiments obtained by a person of ordinary skill in the art based on the embodiments of the present invention without creative work are within the scope of the present invention.
数字信号处理领域, 视频编解码器广泛应用于各种电子设备中, 例如: 移 动电话, 无线装置, 个人数据助理(PDA ), 手持式或便携式计算机, GPS接 收机 /导航器, 照相机, 音频 /视频播放器, 摄像机, 录像机, 监控设备等。 通 常, 这类电子设备中包括视频编码器或视频解码器,视频编码器或视频解码器 可以直接由数字电路或芯片例如 DSP ( digital signal processor )实现, 或者由软 件代码驱动处理器执行软件代码中的流程而实现。 本发明实施例提出了新的像素分类方法,该方法不仅考虑到像素方向性特 征对滤波器系数训练的重要影响,同时考虑到了像素所在区域局部方差对滤波 器强度的影响。 为了便于系数合并, 设计了合理的像素类别的排列方法, 最终 实现编码效率的提升。其中方向性利用梯度计算了图像的局部纹理的方向和强 度, 方向值的分类数量大于或等于复杂度值的分类数量。 参考图 3 , 本发明提供的一种视频图像的像素分类方法的一个实施例, 用 于获得视频图像中的任一像素或像素块的分类, 包括: In the field of digital signal processing, video codecs are widely used in various electronic devices, such as: mobile phones, wireless devices, personal data assistants (PDAs), handheld or portable computers, GPS receivers/navigators, cameras, audio/ Video player, video camera, video recorder, monitoring equipment, etc. Generally, such an electronic device includes a video encoder or a video decoder, and the video encoder or video decoder can be directly implemented by a digital circuit or a chip such as a DSP (digital signal processor), or can be executed by a software code to execute the software in the processor. The process is implemented. The embodiment of the invention proposes a new pixel classification method, which not only considers the important influence of the pixel directional characteristic on the filter coefficient training, but also considers the influence of the local variance of the region where the pixel is located on the filter strength. In order to facilitate the combination of coefficients, a reasonable arrangement of pixel categories is designed, and finally the coding efficiency is improved. The directionality uses the gradient to calculate the direction and intensity of the local texture of the image, and the number of classifications of the direction values is greater than or equal to the number of classifications of the complexity values. Referring to FIG. 3, an embodiment of a pixel classification method for a video image provided by the present invention is used to obtain a classification of any pixel or pixel block in a video image, including:
S301:获得视频图像中的任一像素或像素块对应的方向值; S301: Obtain a direction value corresponding to any pixel or pixel block in the video image;
该像素分类方法可以实现对一个像素的分类, 或者以像素块为单位的分 类。 The pixel classification method can implement classification of one pixel or classification in units of pixel blocks.
像素或者像素块对应的方向值采用四个梯度值计算获得。该步骤的一个实
施方式包括: The direction value corresponding to the pixel or pixel block is calculated using four gradient values. a step of this step The methods include:
计算所述像素或像素块对应的四个梯度值: 水平梯度值、垂直梯度值、 45° 角梯度值和 135°角梯度值; Calculating four gradient values corresponding to the pixel or pixel block: a horizontal gradient value, a vertical gradient value, a 45° angular gradient value, and a 135° angular gradient value;
根据所述四个梯度值, 获得所述像素或像素块对应的方向值。 Obtaining a direction value corresponding to the pixel or the pixel block according to the four gradient values.
以计算位于 ( ,_/)处像素的类别, 梯度算子选择 (-1,2,-1)为例, 用如下公 式计算四个梯度值, grad_h{i,j) X(i + k,j + l- 1)| Taking the class of pixels at ( , _ / ) and the gradient operator selection (-1, 2, -1) as an example, the four gradient values are calculated by the following formula, grad_h{i,j) X(i + k, j + l- 1)|
grad_v(i,j) = ^ *X(i + k,j + l)-X(i + k + \,j + l)\- X(i + k_l,j + /) grad_d(i,j) X(i + k-l,j + 1 + grad_u(i,j) X(i + k + 1 -\)\ Grad_v(i,j) = ^ *X(i + k,j + l)-X(i + k + \,j + l)\- X(i + k_l,j + /) grad_d(i,j) X(i + kl,j + 1 + grad_u(i,j) X(i + k + 1 -\)\
其中 grad— h(i,j)、 grad— v(i,j)、 grad— d^ )和 grad— u^ )分别表示 ( 位置的水 平梯度、 垂直梯度、 45°角梯度和 135°角梯度 4个梯度值。 其中, X代表像素, i代表当前像素的垂直坐标, j代表当前像素的水平坐标, K代表当前像素垂直 坐标的偏移值, 1代表当前像素水平坐标的偏移值 Where grad—h(i,j), grad—v(i,j), grad—d^) and grad—u^) respectively represent (horizontal horizontal gradient, vertical gradient, 45° angular gradient, and 135° angular gradient) 4 gradient values, where X represents a pixel, i represents the vertical coordinate of the current pixel, j represents the horizontal coordinate of the current pixel, K represents the offset value of the current pixel vertical coordinate, and 1 represents the offset value of the current pixel horizontal coordinate.
在获得四个梯度值后,可以根据四个梯度值得到值为 0-3之间的整数 4个方 向值或 0 - 4之间的整数 5个方向值。 After obtaining four gradient values, an integer value of 4 values between 0 and 3 or an integer of 5 directions between 0 and 4 can be obtained from the four gradient values.
S302:获得该像素或像素块对应的复杂度值; 其中, 方向值的分类数量大 于或等于复杂度值的分类数量; S302: Obtain a complexity value corresponding to the pixel or the pixel block, where the number of classifications of the direction value is greater than or equal to the number of classifications of the complexity value;
该步骤的一个实施方式包括:利用量化函数处理所述水平梯度值和垂直梯 度值的梯度和,获得所述像素或像素块对应的复杂度值。复杂度值包括: 0, 1, 2, 3或 0, 1, 2。 One embodiment of the step includes processing a gradient sum of the horizontal gradient value and the vertical gradient value using a quantization function to obtain a complexity value corresponding to the pixel or pixel block. Complexity values include: 0, 1, 2, 3 or 0, 1, 2.
S303:根据该像素或像素块的方向值和复杂度值, 获得该像素或像素块的 分类结果。 S303: Obtain a classification result of the pixel or the pixel block according to the direction value and the complexity value of the pixel or the pixel block.
分类结果 C = A + 4 * D或分类结果 C = A + 3 * D; 其中 A为像素的复杂度 值, D为该像素的方向值。
上述方法可以执行于编码器中也可以执行于解码器中, 当在解码器中时, 该方法还包括:用该分类结果对应的自适应环路滤波器所述像素或像素块进行 滤波。 The classification result C = A + 4 * D or the classification result C = A + 3 * D; where A is the complexity value of the pixel and D is the direction value of the pixel. The above method may be performed in the encoder or in the decoder. When in the decoder, the method further comprises: filtering the pixel or the pixel block by using the adaptive loop filter corresponding to the classification result.
上述实施例, 不仅考虑到像素方向性特征对滤波器系数训练的重要影响, 同时考虑到了像素所在区域局部方差对滤波器强度的影响,方向值的分类数量 大于或等于复杂度值的分类数量。 为了便于系数合并,设计了合理的像素类别 的排列方法, 最终实现编码效率的提升。 参考图 4 , 本发明提供的一种视频图像的像素分类方法的另一个实施例包 括: In the above embodiment, not only the important influence of the pixel directivity feature on the filter coefficient training is considered, but also the influence of the local variance of the region where the pixel is located on the filter strength is considered, and the number of the direction value is greater than or equal to the number of the complexity value. In order to facilitate the combination of coefficients, a reasonable arrangement of pixel categories is designed, and finally the coding efficiency is improved. Referring to FIG. 4, another embodiment of a pixel classification method for a video image provided by the present invention includes:
S401:对编码图像中的任一像素或像素块, 计算像素或像素块对应的四个 梯度值: 水平梯度值、 垂直梯度值、 45°角梯度值和 135°角梯度值; S401: Calculate four gradient values corresponding to the pixel or the pixel block for any pixel or pixel block in the encoded image: horizontal gradient value, vertical gradient value, 45° angular gradient value, and 135° angular gradient value;
计算当前像素局部梯度特征, 以计算位于( ,_/·)处像素的类别, 梯度算子 选择 (-1,2,-1)为例, 用如下公式计算四个梯度: grad_h{i,j) X(i + k,j + l- 1)| Calculate the current local gradient feature of the pixel to calculate the class of the pixel at ( , _ / ·), and select the gradient operator (-1, 2, -1) as an example. Calculate the four gradients with the following formula: grad_h{i,j ) X(i + k,j + l- 1)|
grad_v(i,j) = ^ *X(i + k,j + l)-X(i + k + \,j + l)\- X(i + k_l,j + /) grad_d(i,j) X(i + k-l,j + 1 + grad_u(i,j) X(i + k + 1 -\)\ Grad_v(i,j) = ^ *X(i + k,j + l)-X(i + k + \,j + l)\- X(i + k_l,j + /) grad_d(i,j) X(i + kl,j + 1 + grad_u(i,j) X(i + k + 1 -\)\
其中 grad— h^ )、 grad_v(y')、 grad— d^ )和 grad— u^ )分别表示 (^)位置的水 平梯度、 垂直梯度、 45°角梯度和 135°角梯度 4个梯度值。 其中, X代表像素, i 代表当前像素的垂直坐标, j代表当前像素的水平坐标, K代表当前像素垂直坐 标的偏移值, 1代表当前像素水平坐标的偏移值 Where grad— h^ ), grad_v(y′), grad—d^ ) and grad— u^ ) represent the horizontal gradient of the (^) position, the vertical gradient, the 45° angular gradient and the 135° angular gradient, respectively. . Where X represents a pixel, i represents the vertical coordinate of the current pixel, j represents the horizontal coordinate of the current pixel, K represents the offset value of the current pixel vertical coordinate, and 1 represents the offset value of the current pixel horizontal coordinate.
S402: 根据所述四个梯度值, 获得所述像素或像素块对应的方向值; 具体 的, 选取所述四个梯度值中最小值对应的方向值作为该像素或像素块的方向 值; S402: Obtain a direction value corresponding to the pixel or the pixel block according to the four gradient values. Specifically, select a direction value corresponding to a minimum value of the four gradient values as a direction value of the pixel or the pixel block.
如果四个梯度值中最小值是水平梯度, 则方向值 D = 0;
如果四个梯度值中最小值是 45Q角梯度, 则方向值 D = 1 ; If the minimum of the four gradient values is a horizontal gradient, the direction value D = 0; If the minimum of the four gradient values is a 45 Q angle gradient, the direction value D = 1;
如果四个梯度值中最小值是垂直梯度, 则方向值 D = 2; If the minimum of the four gradient values is a vertical gradient, the direction value D = 2;
如果四个梯度值中最小值是 135°角梯度, 则方向值 D = 3。 If the minimum of the four gradient values is a 135° angular gradient, the direction value D = 3.
S403:利用量化函数, 处理上述水平梯度值和垂直梯度值的梯度和, 获得 所述像素或像素块对应的复杂度值; S403: processing, by using a quantization function, a gradient sum of the horizontal gradient value and the vertical gradient value to obtain a complexity value corresponding to the pixel or the pixel block;
复杂度值可以重用水平梯度值和垂直梯度值,将梯度和量化到 0 - 3之间的 整数; 这样位于 (i,j)处的方差表示为 A = Q(grad_h(i,j) + grad_v(i,j)), 其中 Q(') 表示量化函数, 将梯度和量化到 0-3之间。 The complexity value can reuse the horizontal gradient value and the vertical gradient value, and the gradient sum is quantized to an integer between 0 and 3; thus the variance at (i, j) is expressed as A = Q(grad_h(i,j) + grad_v (i, j)), where Q(') represents the quantization function, and the gradient is quantized to between 0-3.
S404:根据该像素或像素块的方向值和复杂度值, 获得该像素或像素块的 分类结果; S404: Obtain a classification result of the pixel or the pixel block according to the direction value and the complexity value of the pixel or the pixel block.
最终的该像素的分类结果: C = A + 4 * D; 其中 A为像素的梯度和, D为该 像素的方向值。 The final classification result of this pixel: C = A + 4 * D; where A is the gradient of the pixel and D is the direction value of the pixel.
上述方法可以实施在解码端也可以实施在编码端, 进一步的,如果该方法 实施在解码端, 则还包括如下步骤: The foregoing method may be implemented on the decoding end and may also be implemented on the encoding end. Further, if the method is implemented on the decoding end, the method further includes the following steps:
S405:利用该分类结果对应的 ALF滤波器对该像素或像素块进行滤波。 S405: Filter the pixel or the pixel block by using an ALF filter corresponding to the classification result.
ALF需要将一些自身信息压缩编码传递给解码端,解码端在接受到码流后 首先要解码这些信息, 获得 ALF语法元素。 并利用该分类结果对应的 ALF滤波 器对该像素或像素块进行滤波。 ALF needs to pass some self-information compression coding to the decoding end. After receiving the code stream, the decoding end first needs to decode the information to obtain the ALF syntax element. And filtering the pixel or the pixel block by using the ALF filter corresponding to the classification result.
上述实施例, 根据四个梯度值获得像素或像素块的方向值, 方向值包含 4 个值, 复杂度值包含 4个值, 得到 16种像素类别的排列方法, 纹理方向性分类 要大于等于纹理复杂度分类,这种分类方式能充分的挖掘像素或像素块的自身 特性, 有利于滤波器最终的合并操作, 最终实现编码效率的提升。 参考图 5 , 本发明提供的一种视频图像的像素分类方法的另一个实施例包 括: In the above embodiment, the direction value of the pixel or the pixel block is obtained according to the four gradient values, the direction value includes 4 values, the complexity value includes 4 values, and the arrangement method of 16 pixel categories is obtained, and the texture directivity classification is greater than or equal to the texture. Complexity classification, this classification method can fully exploit the characteristics of pixels or pixel blocks, which is beneficial to the final merge operation of the filter, and finally achieves the improvement of coding efficiency. Referring to FIG. 5, another embodiment of a pixel classification method for a video image provided by the present invention includes:
S501: 对编码图像中的任一像素或像素块,计算像素或像素块对应的四个 梯度值: 水平梯度值、 垂直梯度值、 45°角梯度值和 135°角梯度值; S501: Calculate four gradient values corresponding to the pixel or the pixel block for any pixel or pixel block in the encoded image: horizontal gradient value, vertical gradient value, 45° angular gradient value, and 135° angular gradient value;
计算当前像素局部梯度特征, 以计算位于( ,_/· )处像素的类别, 梯度算子
选择 (-1,2,-1)为例, 用如下公式计算四个梯度: grad_h{i,j) X(i + k,j + l- 1)|Calculate the current pixel local gradient feature to calculate the class of pixels at ( , _ / · ), gradient operator Taking (-1, 2, -1) as an example, calculate four gradients using the following formula: grad_h{i,j) X(i + k,j + l- 1)|
grad_v(i,j) = ^ *X(i + k,j + l)-X(i + k + \,j + l)\- X(i + k_l,j + /) grad_d(i,j) X(i + k-l,j + 1 + grad_u(i,j) X(i + k + 1 -\)\ Grad_v(i,j) = ^ *X(i + k,j + l)-X(i + k + \,j + l)\- X(i + k_l,j + /) grad_d(i,j) X(i + kl,j + 1 + grad_u(i,j) X(i + k + 1 -\)\
其中 grad— h^ )、 grad_v(y')、 grad— d^ )和 grad— u^ )分别表示 (^)位置的水 平梯度、 垂直梯度、 45°角梯度和 135°角梯度 4个梯度值。 Where grad— h^ ), grad_v(y′), grad—d^ ) and grad— u^ ) represent the horizontal gradient of the (^) position, the vertical gradient, the 45° angular gradient and the 135° angular gradient, respectively. .
S502: 根据所述四个梯度值, 获得所述像素或像素块对应的方向值; 如果四个梯度值中最大值与最小值之差的绝对值小于一个阙值,则方向值 为第一方向值; 否则,选取四个梯度值中最小值对应的方向值作为该像素或像 素块的方向值; S502: Obtain a direction value corresponding to the pixel or the pixel block according to the four gradient values. If the absolute value of the difference between the maximum value and the minimum value of the four gradient values is less than a threshold value, the direction value is the first direction. Value; otherwise, the direction value corresponding to the minimum of the four gradient values is selected as the direction value of the pixel or the pixel block;
如果梯度最小的值与梯度最大的值得之差的绝对值小于一个阙值,则方向 值 D=0; If the absolute value of the difference between the minimum gradient value and the maximum gradient value is less than a threshold value, the direction value D=0;
否则, 选取所述四个梯度值中最小值对应的方向值作为该像素的方向值: 如果四个梯度值中最小值是水平梯度, 则方向值 D = 0; Otherwise, the direction value corresponding to the minimum value among the four gradient values is selected as the direction value of the pixel: if the minimum value among the four gradient values is a horizontal gradient, the direction value D = 0;
如果四个梯度值中最小值是 45°角梯度, 则方向值 D= 1; If the minimum of the four gradient values is a 45° angular gradient, the direction value D = 1;
如果四个梯度值中最小值是垂直梯度, 则方向值 D = 2; If the minimum of the four gradient values is a vertical gradient, the direction value D = 2;
如果四个梯度值中最小值是 135°角梯度, 则方向值 D = 3。 If the minimum of the four gradient values is a 135° angular gradient, the direction value D = 3.
S503: 利用量化函数, 处理上述水平梯度值和垂直梯度值的梯度和, 获得 所述像素或像素块对应的复杂度值; S503: processing, by using a quantization function, a gradient sum of the horizontal gradient value and the vertical gradient value to obtain a complexity value corresponding to the pixel or the pixel block;
复杂度值可以重用水平梯度值和垂直梯度值,将梯度和量化到 0 - 2之间的 整数; 这样位于 (i,j)处的方差表示为 A = Q(grad_h(i,j) + grad_v(i,j)), 其中 Q(') 表示量化函数, 将梯度和量化到 0-2之间。 The complexity value can reuse the horizontal gradient value and the vertical gradient value, and the gradient sum is quantized to an integer between 0 and 2; thus the variance at (i, j) is expressed as A = Q(grad_h(i,j) + grad_v (i, j)), where Q(') represents the quantization function, and the gradient is quantized to between 0-2.
S504:根据该像素的方向值和复杂度值, 获得该像素的分类结果; 最终的该像素的分类结果: C=A+3 *D; 其中 A为像素的梯度和, D为该 像素的方向值。
上述方法可以实施在解码端也可以实施在编码端, 进一步的,如果该方法 实施在解码端, 则还包括如下步骤: S504: Obtain a classification result of the pixel according to the direction value and the complexity value of the pixel; and finally classify the result of the pixel: C=A+3*D; where A is a gradient of the pixel and D is a direction of the pixel. value. The foregoing method may be implemented on the decoding end and may also be implemented on the encoding end. Further, if the method is implemented on the decoding end, the method further includes the following steps:
S505:利用该分类结果对应的 ALF滤波器对该像素或像素块进行滤波。 ALF需要将一些自身信息压缩编码传递给解码端,解码端在接受到码流后 首先要解码这些信息, 获得 ALF语法元素。 并利用该分类结果对应的 ALF滤波 器对该像素或像素块进行滤波。 S505: Filter the pixel or the pixel block by using an ALF filter corresponding to the classification result. ALF needs to pass some self-information compression coding to the decoding end. After receiving the code stream, the decoding end first needs to decode the information to obtain the ALF syntax element. And filtering the pixel or the pixel block by using the ALF filter corresponding to the classification result.
上述实施例, 根据四个梯度值获得像素或像素块的方向值, 方向值包含 5 个值, 复杂度值包含 3个值, 得到 15种像素类别的排列方法, 纹理方向性分类 要大于等于纹理复杂度分类,这种分类方式能充分的挖掘像素或像素块的自身 特性, 有利于滤波器最终的合并操作, 最终实现编码效率的提升。 本领域普通技术人员可以理解实现上述实施例方法中的全部或部分流程, 是可以通过计算机程序来指令相关的硬件来完成,所述的程序可存储于一计算 机可读取存储介质中 ,该程序在执行时 ,可包括如上述各方法的实施例的流程。 其中,所述的存储介质可为磁碟、光盘、只读存储记忆体(Read-Only Memory, ROM )或随机存储记忆体(Random Access Memory, RAM )等。 与上述方法实施例相关联, 本发明还提供一种视频图像的像素分类装置, 该装置可以位于编码器或解码器中。所述视频图像的像素分类装置可以由硬件 电路来实现, 或者由软件配合硬件来实现。 例如, 参考图 6, 由一个处理器调 用视频图像的像素分类装置来实现对像素的分类。该视频图像的像素分类装置 可以执行上述方法实施例中的各种方法和流程。 参考图 7, 本发明视频图像的像素分类装置的一个实施例, 包括: 方向获得单元 701 , 用于获得视频图像中的任一像素或像素块对应的方向 值; In the above embodiment, the direction value of the pixel or the pixel block is obtained according to the four gradient values, the direction value includes five values, the complexity value includes three values, and the arrangement method of the 15 pixel categories is obtained, and the texture directivity classification is greater than or equal to the texture. Complexity classification, this classification method can fully exploit the characteristics of pixels or pixel blocks, which is beneficial to the final merge operation of the filter, and finally achieves the improvement of coding efficiency. A person skilled in the art can understand that all or part of the process of implementing the above embodiment method can be completed by a computer program to instruct related hardware, and the program can be stored in a computer readable storage medium, the program When executed, the flow of an embodiment of the methods as described above may be included. The storage medium may be a magnetic disk, an optical disk, a read-only memory (ROM), or a random access memory (RAM). In association with the above method embodiments, the present invention also provides a pixel classification apparatus for a video image, which may be located in an encoder or a decoder. The pixel classifying device of the video image may be implemented by a hardware circuit or by software in cooperation with hardware. For example, referring to Figure 6, a pixel classification device that calls a video image by a processor implements classification of pixels. The pixel classifying device of the video image can perform various methods and processes in the above method embodiments. Referring to FIG. 7, an embodiment of a pixel classification apparatus for a video image according to the present invention includes: a direction obtaining unit 701, configured to obtain a direction value corresponding to any pixel or a pixel block in a video image;
复杂度获得单元 702, 用于获得所述像素或像素块对应的复杂度值; 其中, 方向值的分类数量大于或等于复杂度值的分类数量; The complexity obtaining unit 702 is configured to obtain a complexity value corresponding to the pixel or the pixel block, where the number of classifications of the direction value is greater than or equal to the number of classifications of the complexity value;
分类单元 703 , 用于根据该像素的方向值和复杂度值, 获得该像素的分类
结果。 参考图 8, 本发明视频图像的像素分类装置的一个实施例, 包括: 梯度值计算单元 801 , 用于计算所述像素或像素块对应的四个梯度值: 水 平梯度值、 垂直梯度值、 45Q角梯度值和 135°角梯度值; a classifying unit 703, configured to obtain a classification of the pixel according to the direction value and the complexity value of the pixel The result. Referring to FIG. 8, an embodiment of a pixel classifying apparatus for a video image according to the present invention includes: a gradient value calculating unit 801, configured to calculate four gradient values corresponding to the pixel or the pixel block: a horizontal gradient value, a vertical gradient value, and 45 Q angle gradient value and 135° angle gradient value;
获得单元 802, 用于根据所述四个梯度值, 获得所述像素或像素块对应的 方向值; The obtaining unit 802 is configured to obtain, according to the four gradient values, a direction value corresponding to the pixel or the pixel block;
复杂度获得单元 803 , 用于利用量化函数处理所述水平梯度值和垂直梯度 值的梯度和, 获得所述像素或像素块对应的复杂度值; 其中, 方向值的分类数 量大于或等于复杂度值的分类数量; a complexity obtaining unit 803, configured to process a gradient sum of the horizontal gradient value and the vertical gradient value by using a quantization function, to obtain a complexity value corresponding to the pixel or the pixel block; wherein, the number of classifications of the direction value is greater than or equal to the complexity The number of categories of values;
分类单元 804, 用于根据该像素的方向值和复杂度值, 获得该像素的分类 结果。 The classifying unit 804 is configured to obtain a classification result of the pixel according to the direction value and the complexity value of the pixel.
一个实施例中, 复杂度获得单元 803选取所述四个梯度值中最小值对应的 方向值作为该像素或像素块的方向值。 In one embodiment, the complexity obtaining unit 803 selects a direction value corresponding to a minimum value among the four gradient values as a direction value of the pixel or the pixel block.
相应的, 水平梯度值对应的方向值 D = 0; 45°角梯度值对应的方向值0 = Correspondingly, the horizontal gradient value corresponds to the direction value D = 0; 45° angular gradient value corresponds to the direction value 0 =
1; 垂直梯度值对应的方向值 D = 2; 135°角梯度对应的方向值 D = 3; 复杂度 值包括: 0, 1 , 2, 3。 1; the direction value corresponding to the vertical gradient value D = 2; the direction value corresponding to the 135° angular gradient D = 3; the complexity values include: 0, 1 , 2, 3.
该分类结果 C = A + 4 * D;其中 A为像素的复杂度值, D为该像素的方向值。 另一个实施例中,如果所述四个梯度值中最大值与最小值之差的绝对值小 于一个阙值, 复杂度获得单元 803确定所述像素或像素块对应的方向值为第一 方向值; 否则, 所述复杂度获得单元选取所述四个梯度值中最小值对应的方向 值作为该像素的方向值,其中第一方向值为与四个梯度值对应的方向值不同的 值。 The classification result C = A + 4 * D; where A is the complexity value of the pixel and D is the direction value of the pixel. In another embodiment, if the absolute value of the difference between the maximum value and the minimum value of the four gradient values is less than a threshold value, the complexity obtaining unit 803 determines that the direction value corresponding to the pixel or the pixel block is the first direction value. Otherwise, the complexity obtaining unit selects a direction value corresponding to a minimum value among the four gradient values as a direction value of the pixel, wherein the first direction value is a value different from a direction value corresponding to the four gradient values.
相应的, 第一方向值 D = 0; 水平梯度值对应的方向值 D = 1 ; 45°角梯度 值对应的方向值 D = 2; 垂直梯度值对应的方向值 D = 3 ; 135°角梯度对应的方 向值 D = 4; 复杂度值包括: 0, 1 , 2。 Correspondingly, the first direction value D = 0; the horizontal gradient value corresponds to the direction value D = 1; the 45° angular gradient value corresponds to the direction value D = 2; the vertical gradient value corresponds to the direction value D = 3; 135 ° angular gradient The corresponding direction value D = 4; complexity values include: 0, 1 , 2.
分类结果 =八+ 3 * 0; 其中 A为像素的复杂度值, D为该像素的方向值。 上述视频图像的像素分类装置可以在编码器中实现, 也可在解码器中实 现, 当视频图像的像素分类装置应用于编码端时, 还包括:
滤波模块,用于利用该分类结果对应的自适应环路滤波器对所述像素或像 素块进行滤波。 Classification result = eight + 3 * 0; where A is the complexity value of the pixel and D is the direction value of the pixel. The pixel classification device of the above video image may be implemented in an encoder or may be implemented in a decoder. When the pixel classification device of the video image is applied to the encoding end, the method further includes: And a filtering module, configured to filter the pixel or the pixel block by using an adaptive loop filter corresponding to the classification result.
上述实施例不仅考虑到像素方向性特征对滤波器系数训练的重要影响,同 时考虑到了像素所在区域局部方差对滤波器强度的影响,方向值的分类数量大 于或等于复杂度值的分类数量,设计了合理的像素类别的排列方法, 最终实现 编码效率的提升。 The above embodiment not only considers the important influence of the pixel directivity feature on the filter coefficient training, but also considers the influence of the local variance of the pixel region on the filter strength. The number of the direction value is greater than or equal to the number of the complexity value. A reasonable arrangement of pixel categories is used to achieve an improvement in coding efficiency.
以上所述仅为本发明的几个实施例,本领域的技术人员依据申请文件公开 的可以对本发明进行各种改动或变型而不脱离本发明的精神和范围。 The above is only a few embodiments of the present invention, and those skilled in the art can make various changes or modifications to the invention without departing from the spirit and scope of the invention.
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Claims
1、 一种视频图像的像素分类方法, 对其特征在于, 包括: A pixel classification method for a video image, characterized in that:
获得视频图像中的任一像素或像素块对应的方向值; Obtaining a direction value corresponding to any pixel or pixel block in the video image;
获得所述像素或像素块对应的复杂度值; 其中, 方向值的分类数量大于或 等于复杂度值的分类数量; Obtaining a complexity value corresponding to the pixel or the pixel block; wherein, the number of classifications of the direction value is greater than or equal to the number of classifications of the complexity value;
根据该像素的方向值和复杂度值, 获得该像素的分类结果。 The classification result of the pixel is obtained according to the direction value and the complexity value of the pixel.
2、 根据权利要求 1所述的方法, 其特征在于, 获得视频图像中的任一像 素或像素块对应的方向值包括: 2. The method according to claim 1, wherein obtaining a direction value corresponding to any pixel or pixel block in the video image comprises:
计算所述像素或像素块对应的四个梯度值: 水平梯度值、垂直梯度值、 45° 角梯度值和 135°角梯度值; Calculating four gradient values corresponding to the pixel or pixel block: a horizontal gradient value, a vertical gradient value, a 45° angular gradient value, and a 135° angular gradient value;
根据所述四个梯度值, 获得所述像素或像素块对应的方向值; Obtaining a direction value corresponding to the pixel or the pixel block according to the four gradient values;
所述获得所述像素或像素块对应的复杂度值包括: The obtaining the complexity value corresponding to the pixel or the pixel block includes:
利用量化函数处理所述水平梯度值和垂直梯度值的梯度和,获得所述像素 或像素块对应的复杂度值。 A gradient sum of the horizontal gradient value and the vertical gradient value is processed by a quantization function to obtain a complexity value corresponding to the pixel or pixel block.
3、 根据权利要求 2所述的方法, 其特征在于, 根据所述四个梯度值, 获 得所述像素或像素块对应的方向值包括: The method according to claim 2, wherein, according to the four gradient values, obtaining a direction value corresponding to the pixel or the pixel block comprises:
选取所述四个梯度值中最小值对应的方向值作为该像素或像素块的方向 值。 A direction value corresponding to a minimum value among the four gradient values is selected as a direction value of the pixel or the pixel block.
4、 根据权利要求 3所述的方法, 其特征在于, 所述水平梯度值对应的方 向值 D = 0; 所述 45°角梯度值对应的方向值 D = 1 ; 所述垂直梯度值对应的方 向值 D = 2; 所述 135Q角梯度对应的方向值 D = 3; 所述复杂度值包括: 0, 1 , 2, 3。 The method according to claim 3, wherein the horizontal gradient value corresponds to a direction value D = 0; the 45° angular gradient value corresponds to a direction value D = 1; The direction value D = 2; the direction value corresponding to the 135 Q angle gradient is D = 3; the complexity value includes: 0, 1 , 2, 3.
5、 根据权利要求 4所述的方法, 其特征在于, 根据该像素的方向值和梯 度和, 获得该像素的分类结果包括: 分类结果 =八+ 4 * 0; 其中 A为像素的 复杂度值, D为该像素的方向值。 The method according to claim 4, wherein the classification result of the pixel is obtained according to the direction value and the gradient sum of the pixel: the classification result=eight+4*0; wherein A is a complexity value of the pixel , D is the direction value of the pixel.
6、 根据权利要求 2所述的方法, 其特征在于, 根据所述四个梯度值, 获 得所述像素或像素块对应的方向值包括: The method according to claim 2, wherein, according to the four gradient values, obtaining a direction value corresponding to the pixel or the pixel block comprises:
如果所述四个梯度值中最大值与最小值之差的绝对值小于一个阙值,则确 定所述像素或像素块对应的方向值为第一方向值; 否则,选取所述四个梯度值 中最小值对应的方向值作为该像素的方向值,其中第一方向值为与四个梯度值 对应的方向值不同的值。 If the absolute value of the difference between the maximum value and the minimum value of the four gradient values is less than a threshold value, determining that the direction value corresponding to the pixel or the pixel block is the first direction value; otherwise, selecting the four gradient values The direction value corresponding to the medium minimum value is taken as the direction value of the pixel, wherein the first direction value is the same as the four gradient values The corresponding direction value is different.
7、 根据权利要求 6所述的方法, 其特征在于, 所述第一方向值 D = 0; 所 述水平梯度值对应的方向值 D = 1 ; 所述 45°角梯度值对应的方向值 D = 2; 所 述垂直梯度值对应的方向值 D = 3; 所述 135°角梯度对应的方向值 D = 4; 所 述复杂度值包括: 0, 1 , 2。 The method according to claim 6, wherein the first direction value D = 0; the horizontal gradient value corresponding to the direction value D = 1; the 45° angular gradient value corresponding to the direction value D = 2; the vertical gradient value corresponds to a direction value D = 3; the 135 ° angular gradient corresponds to a direction value D = 4; the complexity value includes: 0, 1 , 2.
8、 根据权利要求 7所述的方法, 其特征在于, 根据该像素的方向值和复 杂度值, 获得该像素的分类结果包括: 分类结果 =八+ 3 * 0; 其中 A为像素 的复杂度值, D为该像素的方向值。 The method according to claim 7, wherein the classification result of the pixel is obtained according to the direction value and the complexity value of the pixel: the classification result=eight+3*0; wherein A is the complexity of the pixel Value, D is the direction value of the pixel.
9、 根据权利要求 1所述的方法, 其特征在于, 还包括: 9. The method according to claim 1, further comprising:
利用该分类结果对应的自适应环路滤波器对所述像素或像素块进行滤波。 The pixel or pixel block is filtered using an adaptive loop filter corresponding to the classification result.
10、 一种视频图像的像素分类装置, 其特征在于, 包括: 10. A pixel classification device for video images, comprising:
方向获得单元, 用于获得视频图像中的任一像素或像素块对应的方向值; 复杂度获得单元, 用于获得所述像素或像素块对应的复杂度值; 其中, 方 向值的分类数量大于或等于复杂度值的分类数量; a direction obtaining unit, configured to obtain a direction value corresponding to any pixel or a pixel block in the video image; a complexity obtaining unit, configured to obtain a complexity value corresponding to the pixel or the pixel block; wherein, the number of the direction value is greater than Or the number of classifications equal to the complexity value;
分类单元,用于根据该像素的方向值和复杂度值,获得该像素的分类结果。 And a classification unit, configured to obtain a classification result of the pixel according to the direction value and the complexity value of the pixel.
11、 根据权利要求 10所述的装置, 其特征在于, 所述方向获得单元包括: 梯度值计算单元, 用于计算所述像素或像素块对应的四个梯度值: 水平梯 度值、 垂直梯度值、 45Q角梯度值和 135Q角梯度值; The apparatus according to claim 10, wherein the direction obtaining unit comprises: a gradient value calculating unit, configured to calculate four gradient values corresponding to the pixel or the pixel block: a horizontal gradient value, a vertical gradient value , 45 Q angle gradient values and 135 Q angle gradient values;
获得单元, 用于根据所述四个梯度值, 获得所述像素或像素块对应的方向 值; And an obtaining unit, configured to obtain, according to the four gradient values, a direction value corresponding to the pixel or the pixel block;
其中, 复杂度获得单元, 用于利用量化函数处理所述水平梯度值和垂直梯 度值的梯度和, 获得所述像素或像素块对应的复杂度值。 The complexity obtaining unit is configured to process the gradient sum of the horizontal gradient value and the vertical gradient value by using a quantization function to obtain a complexity value corresponding to the pixel or the pixel block.
12、 根据权利要求 11所述的装置, 其特征在于, 所述复杂度获得单元选 取所述四个梯度值中最小值对应的方向值作为该像素或像素块的方向值。 The apparatus according to claim 11, wherein the complexity obtaining unit selects a direction value corresponding to a minimum value among the four gradient values as a direction value of the pixel or the pixel block.
13、 根据权利要求 12所述的装置, 其特征在于, 所述水平梯度值对应的 方向值 D = 0; 所述 45°角梯度值对应的方向值 D = 1; 所述垂直梯度值对应的 方向值 D = 2; 所述 135°角梯度对应的方向值 D = 3; 所述复杂度值包括: 0, 1 , 2, 3。 The device according to claim 12, wherein the horizontal gradient value corresponds to a direction value D = 0; the 45° angular gradient value corresponds to a direction value D = 1; The direction value D = 2; the 135° angular gradient corresponds to a direction value D = 3; the complexity value includes: 0, 1 , 2, 3.
14、 根据权利要求 13所述的装置, 其特征在于, 所述分类结果 C = A + 4 * D; 其中 A为像素的复杂度值, D为该像素的方向值。 14. The apparatus according to claim 13, wherein the classification result C = A + 4 * D; wherein A is a complexity value of the pixel, and D is a direction value of the pixel.
15、 根据权利要求 11所述的装置, 其特征在于, 如果所述四个梯度值中 最大值与最小值之差的绝对值小于一个阙值,所述复杂度获得单元确定所述像 素或像素块对应的方向值为第一方向值; 否则, 所述复杂度获得单元选取所述 四个梯度值中最小值对应的方向值作为该像素的方向值,其中第一方向值为与 四个梯度值对应的方向值不同的值。 15. The apparatus according to claim 11, wherein the complexity obtaining unit determines the pixel or pixel if an absolute value of a difference between a maximum value and a minimum value among the four gradient values is less than a threshold value The direction value corresponding to the block is a first direction value; otherwise, the complexity obtaining unit selects a direction value corresponding to a minimum value among the four gradient values as a direction value of the pixel, where the first direction value is four gradients The value corresponding to the direction value is different.
16、 根据权利要求 15所述的装置, 其特征在于, 所述第一方向值 D = 0; 所述水平梯度值对应的方向值 D = 1 ; 所述 45°角梯度值对应的方向值 D = 2; 所述垂直梯度值对应的方向值 D = 3 ; 所述 135°角梯度对应的方向值 D = 4; 所述复杂度值包括: 0, 1 , 2。 The device according to claim 15, wherein the first direction value D = 0; the horizontal gradient value corresponds to a direction value D = 1; and the 45° angular gradient value corresponds to a direction value D = 2; the vertical gradient value corresponds to a direction value D = 3; the 135 ° angular gradient corresponds to a direction value D = 4; the complexity value includes: 0, 1 , 2.
17、 根据权利要求 16所述的装置, 其特征在于, 所述分类结果 C = A + 3 17. Apparatus according to claim 16 wherein said classification result C = A + 3
* D; 其中 A为像素的复杂度值, D为该像素的方向值。 * D; where A is the complexity value of the pixel and D is the direction value of the pixel.
18、 根据权利要求 10所述的装置, 其特征在于, 还包括: The device according to claim 10, further comprising:
滤波模块,用于利用该分类结果对应的自适应环路滤波器对所述像素或像 素块进行滤波。 And a filtering module, configured to filter the pixel or the pixel block by using an adaptive loop filter corresponding to the classification result.
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JPWO2017191749A1 (en) * | 2016-05-02 | 2019-03-07 | ソニー株式会社 | Image processing apparatus and image processing method |
CN109862374A (en) * | 2019-01-07 | 2019-06-07 | 北京大学 | A kind of adaptive loop filter method and device |
CN113382257B (en) * | 2021-04-19 | 2022-09-06 | 浙江大华技术股份有限公司 | Encoding method, encoding device, electronic device and computer-readable storage medium |
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