Fast CU Partition Decision Algorithm for AVS3 Intra Coding
Autor: | Shiyi Liu, Zhenyu Wang, Ronggang Wang, Feng Wang, Tong Wu, Rongjie Wang |
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Jazyk: | angličtina |
Rok vydání: | 2021 |
Předmět: |
General Computer Science
Computer science Carry (arithmetic) texture complexity analysis General Engineering 030229 sport sciences 02 engineering and technology Partition (database) AVS3 gradient 03 medical and health sciences Tree (data structure) extend quad-tree 0302 clinical medicine 0202 electrical engineering electronic engineering information engineering 020201 artificial intelligence & image processing General Materials Science lcsh:Electrical engineering. Electronics. Nuclear engineering fast CU partition decision intra coding Algorithm lcsh:TK1-9971 Block (data storage) Coding (social sciences) |
Zdroj: | IEEE Access, Vol 9, Pp 7540-7549 (2021) |
ISSN: | 2169-3536 |
Popis: | The third generation of Audio Video coding Standard (AVS3) is an emerging video coding standard that surpasses High Efficiency Video Coding (HEVC). AVS3 allows flexible block subdivision by applying Quad-Tree (QT), Binary-Tree (BT) plus Extend Quad-Tree (EQT) partition structure, while the increased flexibility comes at the cost of enormous coding complexity. In this paper, an ingenious early termination mechanism is proposed to skip unnecessary exhaustive searches of the whole tree branches. We carry out a series of restrictive measures based on Coding Unit (CU) size and iteration status to make the sophisticated EQT split mode concentrate more on small CUs with complex texture structure. Historical QTBT partition information is also adopted as an important factor to skip EQT split mode in advance. Meanwhile, a fast CU partition algorithm based on the gradient is proposed to skip horizontal or vertical BT/EQT partition of CUs with prominent texture structure in another direction, in which early termination can be directly conducted in homogenous areas at the same time. Extensive experiments demonstrate that the proposed method can save 43% encoding time with only 0.53% BDBR increase on average under All Intra(AI) configuration, which outperforms the preexisting fast algorithms. |
Databáze: | OpenAIRE |
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