Scalable Intra Coding Optimization for Video Coding

被引:0
|
作者
Zhang, Jiaqi [1 ,2 ]
Wang, Meng [3 ]
Jia, Chuanmin [4 ]
Wang, Shanshe [4 ]
Ma, Siwei [4 ]
Gao, Wen [4 ]
机构
[1] Chinese Acad Sci, Inst Comp Technol, Key Lab Intelligent Informat Process, Beijing 100190, Peoples R China
[2] Univ Chinese Acad Sci, Beijing 100049, Peoples R China
[3] City Univ Hong Kong, Dept Comp Sci, Hong Kong, Peoples R China
[4] Peking Univ, Sch Comp Sci, Natl Engn Res Ctr Visual Technol, Beijing 100871, Peoples R China
基金
中国国家自然科学基金;
关键词
Encoding; Complexity theory; Optimization; Standards; Transforms; Electronic mail; Urban areas; AVS3; block partition; inherited information; intra coding optimization; DEPTH DECISION; PREDICTION; PARTITION; ALGORITHM;
D O I
10.1109/TCSVT.2022.3174214
中图分类号
TM [电工技术]; TN [电子技术、通信技术];
学科分类号
0808 ; 0809 ;
摘要
Flexible block partition and newly adopted intra coding tools bring significant performance improvement for next generation video coding, and meanwhile introduce non-negligible encoding complexity increment. This paper presents a scalable intra coding optimization (SICO) scheme for the third generation of audio video coding standard (AVS3). The complexity distribution and inheriting relationship among different partitioning, as well as intra prediction modes, are systematically analyzed. Subsequently, low-complexity algorithms are proposed, which could early exclude unlikely coding modes safely. In particular, a data-driven binary classifier is elegantly trained for the determination of coding unit partitioning. Moreover, the preliminary coding information can be exhaustively utilized for the mode decision in a low-cost manner. The proposed method provides scalable intra coding optimizing solutions, which is eligible to cater to various application scenarios. Experimental results show that the proposed method could achieve a wide range of encoding complexity reduction from 18% to 76% with moderate compression performance loss. One implementation of the proposed method has been adopted to the AVS3 reference software.
引用
收藏
页码:7092 / 7106
页数:15
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