CN102647593B - AVS (Audio Video Standard) intra mode decision method and AVS intra mode decision device - Google Patents
AVS (Audio Video Standard) intra mode decision method and AVS intra mode decision device Download PDFInfo
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Abstract
The invention discloses an AVS (Audio Video Standard) intra mode decision device, comprising an intra mode decision scheduling control module, an intra prediction module, a rate-distortion cost calculation and mode decision module and an intra mode decision output module. The intra mode decision scheduling control module is used for controlling a series of processing flows, such as input, command control, function scheduling and data output of the intra prediction module, the rate-distortion cost calculation and mode decision module and the intra mode decision output module; the intra prediction module is used for generating the corresponding prediction data in each mode of each data block so as to enter a rate-distortion optimization flow line, and the intra prediction module performs intra prediction by reconstructed data; the rate-distortion cost calculation and mode decision module is used for calculating the rate-distortion cost of each mode, simultaneously performing intra mode decision and outputting the result to the intra mode decision output module; and the intra mode decision output module is used for outputting the mode information of the optimal mode, the reconstructed data and the entropy coding information. Meanwhile, the invention also discloses an AVS intra mode decision algorithm.
Description
Technical field
The present invention relates to digital video decoding technical field, relate in particular to a kind of AVS frame mode decision-making technique and device.
Background technology
In order to adapt to the high standard demand of the compression to moving image such as modern digital television broadcasting, digital storage media, network flow-medium, multimedia communication, second generation information source coding AVS (the Advanced coding of audio and vide) standard of China autonomous innovation research and development is arisen at the historic moment, and its relatively low complexity and outstanding coding efficiency become of field in Digital Media and have the strength of competitive strength.Field of video compression for eliminate spatial redundancies H.264/AVC standard first multi-direction spatial domain infra-frame prediction is introduced to application, received good space compression effect.AVS standard has been introduced intraframe prediction algorithm equally, but relatively H.264/AVC AVS standard has taked 8 × 8 larger prediction pieces, and has used less predictive mode to carry out infra-frame prediction.However, in the situation that various frame modes exist, select optimum coding mode to reach optimum encoding efficiency in cataloged procedure in the multi-mode of still will comforming, like this, frame mode decision-making just becomes the focus of research.
At present main frame mode decision-making technique is mainly based on absolute difference and (SAD) and the strategy such as rate-distortion optimization (RDO), the method of rate-distortion optimization in performance (RDO) is than absolute difference and (SAD) can be with the gain of average 0.5db left and right, but the computation complexity of superior decision-making performance need relative complex, researcher is that the strategy addressing this problem roughly has, the first reduces the model number of selecting, it two is to simplify rate distortion computation model, and distortion and code check are adopted to the methods such as approximate calculation.But such method is only the angle from improving performance optimized algorithm merely, does not consider the impact that hardware realizability is brought in practical application.Cause theory innovation to be difficult to better be applied even more extensively among technical applications and go.
Summary of the invention
How the technical problem that the present invention solves is, in the situation that guaranteeing objective high-quality performance, greatly to reduce the complexity of device.
In order to overcome the above problems, the invention discloses a kind of AVS frame mode decision making device, comprising:
Frame mode decision-making dispatching control module, for input, order control and function scheduling, mode decision and the data output of intra-framed prediction module, rate distortion costs calculating and mode decision module, frame mode decision-making output module, the control of a series of like this handling process;
Intra-framed prediction module, for generation of prediction data corresponding under each pattern of each data block, so that admission rate aberration optimizing streamline, this module is carried out infra-frame prediction by reconstruct data;
Rate distortion costs is calculated and mode decision module, for calculating the rate distortion costs of each pattern, carries out frame mode decision-making simultaneously, and result outputs to frame mode decision-making output module;
Frame mode decision-making output module, this module is for exporting the pattern information of optimization model, and reconstruct data, entropy coded message.
Further, preferred as one, described intra-framed prediction module, comprises predicted portions, data update two large divisions; Predicted portions is supported 5 kinds of patterns of brightness, the prediction of 4 kinds of patterns of colourity; Comprise infra-frame prediction control module, preliminary treatment filtration module and six kinds of modules that predictive mode is corresponding; Data update part comprises the row cache module that 64 × 480bits brightness Y colourity UV data are stored successively, the row buffer memory of a 8 × 17bits, the row cache module of two 8 × 9bits; First pass through data update module, then pass through ranks buffer memory, then enter in the prediction module of a certain pattern through preliminary treatment filtration module again, infra-frame prediction control module is for the control of process.
Further, preferred as one, described rate distortion costs is calculated and mode decision module adopts efficient 5 stage pipeline structure in hardware designs, comprises the horizontal DCT module being linked in sequence, vertical DCT and quantization modules, re-quantization and flat DCT module, contrary vertical DCT module, zigzag scan module, entropy coding module, cost calculating and mode decision module against the current.
The invention also discloses a kind of AVS frame mode decision-making technique simultaneously, comprising:
Step 1, infra-frame prediction obtain the infra-frame prediction data under each pattern, and this step, for all intra prediction modes of AVS, comprises all chrominance block and luminance block;
Step 2, determine pipeline schedule strategy, adopt 5 grades of pipelining schemes, priority scheduling luminance block is carried out flowing water, the problem that the streamline causing for the data dependence solving between infra-frame prediction data block interrupts, the processing of chrominance block is inserted in luminance block schedule gaps, for the pattern of each data block, take enabled mode to carry out in advance the strategy of flowing water simultaneously; Step 3, based on rate distortion costs model, calculation rate distortion cost, first the original pixels of infra-frame prediction data and correspondence position is done to the poor residual error data that goes out, then for residual error data, carry out drawing distortion D with original pixel value summation after integral discrete cosine transform, quantification, inverse quantization, inverse transformation; Quantization parameter is carried out to zigzag scanning, entropy coding obtains the code check R of predict pixel piece simultaneously; According to the distortion obtaining and code rate information, calculate rate distortion costs;
Step 4, frame mode decision-making and data cached renewal, relatively rate distortion costs corresponding to each frame mode through calculating, determine current data block optimal prediction modes, and by the rightmost under current block optimization model and reconstructed pixel Data Update bottom to corresponding row cache and row buffer memory relevant position, for below data block to be processed is carried out to reference data preparation.
Further, preferred as one, described intraprediction unit is supported horizontal pattern, vertical mode, DC mode, lower-left diagonal pattern and 5 kinds of patterns of lower-right diagonal position pattern of luminance block, horizontal pattern, vertical mode, DC mode and 4 kinds of patterns of plane mode of chrominance block.
Further, preferred as one, in described pipeline schedule strategy, data dependency exists only between each piece of luminance block, so first dispatch for the various patterns of luminance block, chrominance block pattern is inserted in luminance block flowing water gap, meanwhile the luminance patterns that does not rely on last luminance block is processed and inserted in flowing water gap, further optimize flowing water strategy.
Further, preferred as one, in described rate distortion costs calculation procedure, under certain pattern, the distortion D of data block and the calculating of code check R are as efficient flowing water algorithm, and calculated distortion D concrete steps comprise: horizontal DCT, vertical DCT, quantification, inverse quantization, against the current flat DCT, contrary vertical DCT, reconstruct data generate, the calculating of distortion D; Calculating code check R concrete steps comprises: the acquisition of the parallel entropy coding in zigzag scan method, N road that horizontal DCT, vertical DCT, quantification, N road are parallel and bit number statistical, code check R.
The present invention has following advantage compared with prior art: by algorithm level optimization, algorithm is transformed into the attainable algorithm of hardware, under the prerequisite of guaranteed performance, significantly reduces the complexity that encoder hardware is realized, considered the method for designing of algorithm and structure; Breaking the data dependency of infra-frame prediction self, optimized pipeline schedule strategy, is that streamline is not forced to because of data dependence interrupt, and significantly improves pipeline efficiency; Classifying rationally modular processing unit, improve the degree of parallelism of circuit, thereby improved disposal ability and the speed of circuit, realized a kind of AVS frame mode decision-making high performance device; Transposition of the present invention has good reliability, maintains higher coding quality in low-bandwidth environment, and requirement of real time can show high-quality video image compression quality under the environment of bandwidth abundance; This device can provide good thinking and method for inter mode decision in addition.
Accompanying drawing explanation
When considered in conjunction with the accompanying drawings, by the detailed description with reference to below, can more completely understand better the present invention and easily learn wherein many advantages of following, but accompanying drawing described herein is used to provide a further understanding of the present invention, form a part of the present invention, schematic description and description of the present invention is used for explaining the present invention, does not form inappropriate limitation of the present invention, wherein:
Fig. 1 is frame mode decision making device structure chart;
Fig. 2 is intra-framed prediction module structure chart;
Fig. 3 is infra-frame prediction row cache and row buffer organization figure;
Fig. 4 is that rate distortion costs is calculated and mode decision modular structure figure;
Fig. 5 is frame mode decision making algorithm flow chart of the present invention;
Fig. 6 is frame mode decision-making pipeline schedule policy map.
Embodiment
Referring to Fig. 1-6 pair embodiments of the invention, describe.
For above-mentioned purpose, feature and advantage can be become apparent more, below in conjunction with the drawings and specific embodiments, the present invention is further detailed explanation.
With reference to Fig. 1, be frame mode decision making device structure chart of the present invention, this device comprises intra-framed prediction module 100, rate distortion costs is calculated and mode decision module 101, frame mode decision-making output module 102 and frame mode decision-making dispatching control module 103.
Intra-framed prediction module 100, for generate each pattern prediction data, upgrade the reconstruct data of row cache 201 and row buffer memory 202.100 calculate according to side output module 102 and rate distortion costs with frame mode and mode decision mould 101 is connected, and obtain reconstruct data from 102, and the prediction data of each pattern is exported to 101.Rate distortion costs is calculated and mode decision module 101, for the rate distortion costs of carrying out under each pattern, calculate and go out optimization model from various enabled mode decision-makings, it is connected with intra-framed prediction module 100, frame mode decision-making output module 102, obtain prediction data from 100, the prediction data under optimization model and optimization model is exported to 102.Frame mode decision-making output module 102 and rate distortion costs calculate and mode decision module 101, intra-framed prediction module 100 are connected.Be used for the output of the relevant information of optimization model.Frame mode decision-making dispatching control module 103 all has control line to be connected with every other module, is the scheduling controlling unit of whole device, has determined workflow and the flowing water strategy of whole device.
With reference to Fig. 2, be the cut-away view of frame mode decision making device submodule intra-framed prediction module 100 of the present invention, the solid line with arrow in figure is data wire, the dotted line with arrow is control line.Data update module 200 will carry out Data Update for the data in row cache 201 and row buffer memory 202 after obtaining reconstruct data information.It is connected preliminary treatment filtration module 203 with buffer memory 201,202, and the data message that obtains current block from ranks buffer memory carries out preliminary treatment filtering operation, and object is to be convenient to next step to carry out predicted operation for concrete pattern; Also be connected with 205 to 210 modules, the required pretreated information of forecasting of predicting unit of various patterns is provided simultaneously.205 to 210 is the predicting unit module of concrete pattern, is followed successively by vertical mode, horizontal pattern, DC mode, plane mode, lower-left diagonal pattern, lower-right diagonal position pattern.Their function is to carry out predicted operation according to the operation rules of this pattern, and exports corresponding prediction data.211 is MUX, and function is the prediction data on the concrete road of data, and it is connected with Unit 205 to 210.204 is infra-frame prediction control unit, for judging the enabled mode of current data block and whole infra-frame prediction internal module operation being controlled.Due to the position difference of data block in two field picture, on some boundary position, some pattern is disabled, for example, at two field picture data line piece topmost, can not carry out vertical mode prediction.
With reference to Fig. 3, be the interior tissue figure of frame mode decision making device submodule intra-framed prediction module of the present invention 100 inner ranks buffer memorys 201 and 202.Row cache is used for storing the row pixel data of a whole frame width above adjacent current prediction piece, comprises brightness and colourity; Row buffer memory is used for storing 17 luminance pixels and 9 chroma pixels that are close to the current prediction data piece left side.And along with the processing of data block is dynamically to data cached maintenance and renewal, while guaranteeing infra-frame prediction, from relevant position, obtain reference pixel exactly.The every a line of row cache can be stored 8 pixel datas, i.e. 64bits, and for 1080p image in different resolution, two field picture width 1920 pixels, need 240 degree of depth storage brightness datas, the chroma data of 120 × 2 degree of depth.The institutional framework that row cache has taked YUV to store successively, the institutional framework of formation 64 × 480bit.Row buffer memory adopts the separately strategy of storage of YUV, and space size is respectively 8 × 17bits, 8 × 9bits and 8 × 9bits, and wherein row buffer memory comprises: brightness Y row buffer memory 301, colourity U row buffer memory 302, colourity V row buffer memory 303.
With reference to Fig. 4, for frame mode decision making device submodule rate distortion costs of the present invention is calculated and mode decision module 101 structure charts.It is an efficient data-driven pipeline organization, comprises residual error and horizontal DCT processing module 400, vertical DCT and quantification treatment module 401, zigzag scan module 402, code check statistical module 403, inverse quantization and flat DCT variation module 404, the vertical conversion module 405 of inverse DCT, cost calculating and mode selection module 406 and respectively the ping-pong buffer memory 407 between the pipelining-stage of front and back against the current.Wherein:
Residual error and horizontal DCT processing module 400 for calculating the predict pixel of current block and the difference of original pixels, are carried out horizontal dct transform to difference simultaneously, conversion result store in ping-pong buffer memory below; Vertical DCT is connected with the ping-pong buffer memory 407 between quantification treatment module 401 and module 400, and for the result of module 400 is carried out to vertical dct transform and quantization operation, and the result store after a quantification is in ping-pong buffer memory below; Zigzag scan module 402 and inverse quantization and against the current flat DCT change module 404, ping-pong buffer memory all and between module 401 is connected, module 402 is for carrying out zigzag scanning to quantization parameter, generate (run, level) pair, determine the code table of entropy coding simultaneously, and result is outputed in ping-pong buffer memory below, and module 404 is for carrying out inverse quantization and flat dct transform operation against the current to the coefficient after quantizing; Code check statistical module 403, is connected with zigzag scanning 402 ping-pong buffer memory below, for (run, level) pair is carried out to entropy encoding operation, counts code check R simultaneously; The ping-pong buffer memory that the vertical conversion module 405 of inverse DCT is exported with module 404 is connected, and the output of module 404 is carried out to contrary vertical dct transform operation, and result is outputed in rear class ping-pong buffer memory; Cost is calculated and mode selection module 406 is connected with code check statistical module 403, the vertical conversion module 405 of inverse DCT ping-pong buffer memory below simultaneously, complete the calculating of distortion D, and according to R calculation rate distortion cost RDcost, last, based on RDcost, carry out mode decision, and result is exported.
With reference to Fig. 5, be the frame mode decision making algorithm flow chart of invention, specifically comprise the following steps:
After start-up mode decision-making starts 500, first carry out initialization step 501, in initialized process, the parameter needing to model selection configuration, mainly uses picture traverse, quantization step; Start afterwards 502 pairs of available frame internal schemas and judge, because the position difference of data block in residing two field picture, some pattern is disabled, such as the uppermost data line piece of image can not carry out vertical mode prediction.After drawing available frame internal schema, enter step 503 and under certain pattern of several piece of pre-treatment, carry out infra-frame prediction to working as, obtain the prediction data under this pattern, by data, the high performance pipeline scheduling strategy proposing according to us subsequently, carrying out step is 504 pipeline schedules, calculate the rate distortion costs 505 of this pattern thereupon, then judge whether to handle an enabled mode 506 that data block is all: when all enabled mode dispatch deals of a data block do not finish, can repeat step 503 according to our the pipeline schedule strategy of design, 504, 505, 506, otherwise by entering step 507, carry out the model selection of current block, the reconstruct data under current data block optimization model is updated in the row cache and row buffer memory in intra-framed prediction module subsequently.Then enter step 508 and judge whether to handle all data blocks: if the mode decision of all data blocks all draw, enter step 510 and finish whole processing procedure; Otherwise can continue to carry out 503 to 509 steps.It should be noted that whole 503 to 509 steps all in the high performance pipeline scheduling strategy shown in design drawing 6 of the present invention, are not traditional serial process mode.
With reference to Fig. 6, be frame mode decision-making pipeline schedule policy map of the present invention, in figure, the square block of different shades represents different data blocks, B00, B01, B02, B03, U, V represent No. 1 piece to 4 piece of brightness successively, colourity U piece and colourity V piece.Belong to a certain concrete pattern of this data block of numeral marking in the square block of same data block.In luminance block 1,2,3,4,5 represents vertical mode, horizontal pattern, DC mode, lower-left diagonal pattern and lower-right diagonal position pattern successively, and what colourity took soon 1,2,3,4 represents vertical mode, horizontal pattern, DC mode and plane mode successively.
A) dispatch first successively vertical mode, horizontal pattern, DC mode, lower-left diagonal pattern, the lower-right diagonal position pattern of No. 0 piece of brightness;
B), for streamline is not interrupted by the data dependency between 0, No. 1 piece of brightness, the horizontal pattern of the vertical mode of No. 1 piece of brightness and No. 2 pieces of brightness can be dispatched at once successively, does not need to wait for the reconstruct data of No. 0 piece of brightness;
C) because there is no data dependence between chrominance block and luminance block, the and then horizontal pattern of No. 2 pieces of brightness, the vertical mode of colourity U piece and horizontal pattern will be dispatched successively;
D) No. 0 piece reconstruct data of now brightness can be used, horizontal pattern, DC mode, lower-left diagonal pattern and the lower-right diagonal position pattern of dispatching No. 1 piece of brightness at once;
E), waiting in the time space that brightness No. 1 piece reconstruct data draws, dispatch successively without the DC mode of the colourity U piece of data dependence, plane mode, the vertical mode of No. 2 pieces of brightness, the vertical mode of colourity V piece;
F) reconstruct data of No. 1 piece of now brightness can be used, and dispatches successively DC mode, lower-left diagonal pattern and the lower-right diagonal position pattern of No. 2 pieces of brightness;
G) waiting in the time space that No. 2 piece reconstruct data of brightness draw, dispatch successively the countless horizontal patterns according to dependent colourity V piece, DC mode, plane mode;
H) No. 2 piece reconstruct data of now brightness can be used, and dispatch successively vertical mode, horizontal pattern, DC mode, lower-left diagonal pattern and the lower-right diagonal position pattern of No. 3 pieces of brightness.
The scheduling completing through above step, streamline will can not interrupted because of infra-frame prediction data dependence, significantly improve the operating efficiency of streamline.
As mentioned above, embodiments of the invention are explained, but as long as not departing from fact inventive point of the present invention and effect can have a lot of distortion, this will be readily apparent to persons skilled in the art.Therefore, within such variation is also all included in protection scope of the present invention.
Claims (7)
1. an AVS frame mode decision making device, is characterized in that, comprising:
Frame mode decision-making dispatching control module, for input, order control and function scheduling, mode decision and the data output of intra-framed prediction module, rate distortion costs calculating and mode decision module, frame mode decision-making output module, the control of a series of like this handling process, comprising:
Determine pipeline schedule strategy, adopt 5 grades of pipelining schemes, priority scheduling luminance block is carried out flowing water, and the processing of chrominance block is inserted in luminance block schedule gaps, for the pattern of each data block, takes enabled mode to carry out in advance the strategy of flowing water simultaneously;
Determine current data block optimal prediction modes, and by the rightmost under current block optimization model and reconstructed pixel Data Update bottom to corresponding row cache and row buffer memory relevant position, for below data block to be processed is carried out to reference data preparation;
Intra-framed prediction module, for generation of prediction data corresponding under each pattern of each data block, so that admission rate aberration optimizing streamline, this module is carried out infra-frame prediction by reconstruct data;
Rate distortion costs is calculated and mode decision module, for calculating the rate distortion costs of each pattern, carries out frame mode decision-making simultaneously, and result outputs to frame mode decision-making output module;
Frame mode decision-making output module, this module is for exporting the pattern information of optimization model, and reconstruct data, entropy coded message.
2. according to a kind of AVS frame mode decision making device shown in claim 1, it is characterized in that described intra-framed prediction module comprises predicted portions, data update two large divisions; Predicted portions is supported 5 kinds of patterns of brightness, the prediction of 4 kinds of patterns of colourity; Comprise infra-frame prediction control module, preliminary treatment filtration module and six kinds of modules that predictive mode is corresponding; Data update part comprises the row cache module that 64 × 480bits brightness Y colourity UV data are stored successively, the row buffer memory of a 8 × 17bits, the row cache module of two 8 × 9bits; Data are first passed through data update module, then pass through ranks buffer memory, then are entering the prediction module of each pattern, the whole processing procedure of infra-frame prediction control module control through preliminary treatment filtration module.
3. according to a kind of AVS frame mode decision making device shown in claim 1, it is characterized in that, described rate distortion costs is calculated and mode decision module adopts efficient 5 stage pipeline structure in hardware designs, comprises the horizontal DCT module being linked in sequence, vertical DCT and quantization modules, re-quantization and flat DCT module, contrary vertical DCT module, zigzag scan module, entropy coding module, cost calculating and mode decision module against the current.
4. an AVS frame mode decision-making technique, is characterized in that, comprising:
Step 1, infra-frame prediction obtain the infra-frame prediction data under each pattern, and this step, for all intra prediction modes of AVS, comprises all chrominance block and luminance block;
Step 2, determine pipeline schedule strategy, adopt 5 grades of pipelining schemes, priority scheduling luminance block is carried out flowing water, and the processing of chrominance block is inserted in luminance block schedule gaps, for the pattern of each data block, take enabled mode to carry out in advance the strategy of flowing water simultaneously; Step 3, based on rate distortion costs model, calculation rate distortion cost, first the original pixels of infra-frame prediction data and correspondence position is done to the poor residual error data that goes out, then for residual error data, carry out drawing distortion D with original pixel value summation after integral discrete cosine transform, quantification, inverse quantization, inverse transformation; Quantization parameter is carried out to zigzag scanning, entropy coding obtains the code check R of predict pixel piece simultaneously; According to the distortion obtaining and code rate information, calculate rate distortion costs;
Step 4, frame mode decision-making and data cached renewal, relatively rate distortion costs corresponding to each frame mode through calculating, determine current data block optimal prediction modes, and by the rightmost under current block optimization model and reconstructed pixel Data Update bottom to corresponding row cache and row buffer memory relevant position, for below data block to be processed is carried out to reference data preparation.
5. according to a kind of AVS frame mode decision-making technique shown in claim 4, it is characterized in that, intra prediction mode comprises horizontal pattern, vertical mode, DC mode, lower-left diagonal pattern and 5 kinds of patterns of lower-right diagonal position pattern of supporting luminance block, supports horizontal pattern, vertical mode, DC mode and 4 kinds of patterns of plane mode of chrominance block.
6. according to a kind of AVS frame mode decision-making technique shown in claim 4, it is characterized in that, in described pipeline schedule strategy, data dependency exists only between each piece of luminance block, so first dispatch for the various patterns of luminance block, chrominance block pattern is inserted in luminance block flowing water gap, meanwhile the luminance patterns that does not rely on last luminance block is processed and inserted in flowing water gap, further optimize flowing water strategy.
7. according to a kind of AVS frame mode decision-making technique shown in claim 4, it is characterized in that, in described rate distortion costs calculation procedure, the distortion D of data block and the calculating of code check R are as efficient flowing water algorithm, and calculated distortion D concrete steps comprise: horizontal DCT, vertical DCT, quantification, inverse quantization, the calculating of flat DCT, contrary vertical DCT, reconstruct data generation, distortion D against the current; Calculating code check R concrete steps comprises: the acquisition of the parallel entropy coding in zigzag scan method, N road that horizontal DCT, vertical DCT, quantification, N road are parallel and bit number statistical, code check R.
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| CN103428501A (en) * | 2013-09-08 | 2013-12-04 | 张新安 | AVS intra-frame prediction mode fast selection algorithm |
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| CN106254866B (en) * | 2016-10-17 | 2018-05-29 | 中国科学技术大学 | Video intra-frame encoding method based on the flexible block order of stratification |
| CN109660794B (en) * | 2018-11-07 | 2020-07-07 | 北京达佳互联信息技术有限公司 | Decision method, decision device and computer readable storage medium for intra prediction mode |
| CN113382239A (en) * | 2020-02-25 | 2021-09-10 | 北京君正集成电路股份有限公司 | Rapid residual error code rate cost calculation method suitable for H265 |
| CN111918058B (en) * | 2020-07-02 | 2022-10-28 | 北京大学深圳研究生院 | Hardware-friendly intra prediction mode fast determination method, device and storage medium |
| CN112911285B (en) * | 2021-01-26 | 2023-04-07 | 北京博雅慧视智能技术研究院有限公司 | Hardware encoder intra mode decision circuit, method, apparatus, device and medium |
| CN113630596A (en) * | 2021-06-25 | 2021-11-09 | 杭州未名信科科技有限公司 | AVS3 intra-frame prediction mode rough selection method, system and medium |
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Application publication date: 20120822 Assignee: Boya cloud (Beijing) Technology Co., Ltd. Assignor: Peking University Contract record no.: 2017990000366 Denomination of invention: AVS (Audio Video Standard) intra mode decision method and AVS intra mode decision device Granted publication date: 20140416 License type: Exclusive License Record date: 20170908 |
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