文献类型：会议论文

英文题名：Fast Algorithm Based on Non-first Pre-coding Skip for AVS3 Intra Coding

作者：Cao, Xueyan[1]; Lin, Tao[1]; Zhao, Liping[2]; Yang, Yufen[3]; Zhou, Kailun[1]; Wang, Shuhui[1]

机构：[1] Tongji University, College of Electronic and Information Engineering, Shanghai, China; [2] Shaoxing University, School of Computer Science and Engineering, Shaoxing, China; [3] Shanghai Institute of Technology, School of Computer Science and Information Engineering, Shanghai, China

会议论文集：2023 8th International Conference on Signal and Image Processing, ICSIP 2023

会议日期：July 8, 2023 - July 10, 2023

会议地点：Wuxi, China

语种：英文

外文关键词：Binary trees - Image coding - Video signal processing

外文摘要：The third generation of Audio Video coding Standard (AVS3) adopts multi-type tree, including Quad-Tree (QT), Binary-Tree (BT) plus Extend Quad-Tree (EQT), partition structure. During multi-type tree recursive pre-coding process of encoding, each Coding Units (CU) of each Size at each Location (CUeSeL) of the picture is repeatedly pre-coded many times when visiting each branch of each tree. Although there is early termination mechanism, the number of visit for each CUeSeL is still very high and up to more than twenty. This process brings very high coding complexity. To reduce the coding complexity of AVS3, this paper proposes a method named non-first pre-coding skip (NFPS) for CUeSeL. The contributions of the paper are as follows. In I picture, for a CU with top-left location (x, y), if both x and y are multiples of 64, then each non-first pre-coding is skipped and the coding result of the first pre-coding is reused for each non-first pre-coding. In non-I picture, for a CU with top-left location (x, y), if both x and y are multiples of 64 and a set of conditions is satisfied, then each non-first pre-coding is skipped and the coding result of the first pre-coding is reused for each non-first pre-coding. The experimental results demonstrate that NFPS has a negligible impact on coding efficiency under All intra (AI), Low Delay B (LDB), Random Access (RA) configurations, and coding runtime is reduced by 6% for AI and almost not changed for LDB and RA. ? 2023 IEEE.