A hardware architecture of skip/direct mode for AVS3

Yingbo Wen; Guoqing Xiang; Yunyao Yan; Xizhong Zhu; Xiaofeng Huang; Peng Zhang; Wei Yan

doi:10.1117/12.2643010

12 October 2022 A hardware architecture of skip/direct mode for AVS3

Yingbo Wen, Guoqing Xiang, Yunyao Yan, Xizhong Zhu, Xiaofeng Huang, Peng Zhang, Wei Yan

Proceedings Volume 12342, Fourteenth International Conference on Digital Image Processing (ICDIP 2022); 1234228 (2022) https://doi.org/10.1117/12.2643010
Event: Fourteenth International Conference on Digital Image Processing (ICDIP 2022), 2022, Wuhan, China

Abstract

Skip/direct mode is one of the inter prediction modes in video coding, which achieves a high coding performance. In Audio and Video coding Standard-3(AVS3), skip/direct has improved more performance with more candidate modes. The candidate mode list is generated by numerous prediction directions with corresponded predicted motion vectors. However, it will result in higher computation complexities and challenges to parallel computation, especially for the hardware implementation. For resolving the problem, we propose a hardware architecture of skip/direct mode with a fast motion vector prediction (MVP) algorithm in this paper. Our architecture is designed with efficient pipeline schedules. And the fast MVP algorithm can reduce the number of MVP candidates efficiently. The fast MVP method is introduced by setting a search window, some unnecessary MVP are skipped, thereby reducing the computational complexity firstly. Then the proposed hardware architecture is given with efficient pipeline schedules in detail. The experimental results show that our architecture is able to meet the requirement of 3840x2160@60FPS with only 0.48% and 0.42% BD-Rate increase under the low delay P (LDP) and random access (RA) configurations, respectively.

Citation Download Citation

Yingbo Wen, Guoqing Xiang, Yunyao Yan, Xizhong Zhu, Xiaofeng Huang, Peng Zhang, and Wei Yan "A hardware architecture of skip/direct mode for AVS3", Proc. SPIE 12342, Fourteenth International Conference on Digital Image Processing (ICDIP 2022), 1234228 (12 October 2022); https://doi.org/10.1117/12.2643010

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