TY - GEN
T1 - Efficient Algorithm and Hardware Architecture for Rate Estimation in Mode Decision of AVS3
AU - Yan, Yunyao
AU - Xiang, Guoqing
AU - Xie, Xiaodong
AU - Jia, Huizhu
AU - Li, Yuan
AU - Zhang, Peng
AU - Chen, Jie
N1 - Publisher Copyright:
© 2022 IEEE.
PY - 2022
Y1 - 2022
N2 - Towards enabling advanced video coding for emerging ap-plications, the AVS3 standard has been developed recently, achieving twice the coding efficiency of the AVS2 stan-dard through complex coding tools including advanced rate-distortion optimization (RDO) to select the best mode. The bit-rates are produced with the Advanced-Entropy-Coding (AEC) in the RDO process of AVS3. However, AEC dom-inates the time complexity of RDO and among the steps, con-text updating and interval subdivision are performed recur-sively, which is not conducive to real-time application, espe-cially for the hardware implementation. Thus this paper pro-poses an adaptive rate estimation algorithm with a piece-wise linear function that is very friendly to hardware implemen-tation to accelerate the rate estimation process in the RDO for AVS3 practical applications. The proposed architecture can meet the requirement of 4K@120fps ultra-high-definition videos at 200 MHz, whereas the BD-Rate increases only by 0.67% under the All-Intra (AI) configuration.
AB - Towards enabling advanced video coding for emerging ap-plications, the AVS3 standard has been developed recently, achieving twice the coding efficiency of the AVS2 stan-dard through complex coding tools including advanced rate-distortion optimization (RDO) to select the best mode. The bit-rates are produced with the Advanced-Entropy-Coding (AEC) in the RDO process of AVS3. However, AEC dom-inates the time complexity of RDO and among the steps, con-text updating and interval subdivision are performed recur-sively, which is not conducive to real-time application, espe-cially for the hardware implementation. Thus this paper pro-poses an adaptive rate estimation algorithm with a piece-wise linear function that is very friendly to hardware implemen-tation to accelerate the rate estimation process in the RDO for AVS3 practical applications. The proposed architecture can meet the requirement of 4K@120fps ultra-high-definition videos at 200 MHz, whereas the BD-Rate increases only by 0.67% under the All-Intra (AI) configuration.
KW - AEC
KW - AVS3
KW - hardware-friendly algorithm
KW - rate estimation
UR - https://www.scopus.com/pages/publications/85137726248
U2 - 10.1109/ICME52920.2022.9858932
DO - 10.1109/ICME52920.2022.9858932
M3 - Conference contribution
AN - SCOPUS:85137726248
T3 - Proceedings - IEEE International Conference on Multimedia and Expo
BT - ICME 2022 - IEEE International Conference on Multimedia and Expo 2022, Proceedings
PB - IEEE Computer Society
T2 - 2022 IEEE International Conference on Multimedia and Expo, ICME 2022
Y2 - 18 July 2022 through 22 July 2022
ER -