Fast Coding Unit Splitting Decisions for the Emergent AVS3 Standard

AVS3 adopts quad-tree (QT) with nested binary tree (BT) and extended quad-tree (EQT) partitioning, which shows promising compression performance when compared to the conventional QT partitioning in AVS2 and HEVC. However, the interleaved and recursive splitting manner significantly increases the computational complexity of the encoder, which may impede the real applications of AVS3. This paper proposes fast coding unit splitting decision methods for QT, BT and EQT partitioning. In particular, the Bayesian decision rule is employed with Skip states, and BT and EQT partitioning can be early terminated. Additionally, the average splitting depth that is produced by BT partitioning, is incorporated as the prior information for terminating the EQT and QT splittings. Moreover, we explore the splitting settings for CUs that are predicted with Skip mode, with the aim of eliminating unnecessary partition attempts. Experimental results show that the proposed fast algorithms are effective and provide a good trade-off between computational complexity and coding performance. In particular, 69% encoding time reduction is achieved with only 0.55% increase in terms of BD-Rate on average, which greatly benefits the practical implementations of the AVS3 in real applications. The proposed methods have been adopted into TAVS3 reference software.

[1]  Wen Gao,et al.  iAVS2: A Fast Intra-Encoding Platform for IEEE 1857.4 , 2017, IEEE Transactions on Circuits and Systems for Video Technology.

[2]  Jizheng Xu,et al.  History-Based Motion Vector Prediction in Versatile Video Coding , 2019, 2019 Data Compression Conference (DCC).

[3]  Wen Gao,et al.  An Overview of AVS2 Standard , 2014 .

[4]  Meng Wang,et al.  Content Based Fast Intra Coding for AVS2 , 2017, 2017 IEEE Third International Conference on Multimedia Big Data (BigMM).

[5]  Shiqi Wang,et al.  Extended Quad-Tree Partitioning for Future Video Coding , 2019, 2019 Data Compression Conference (DCC).

[6]  Munchurl Kim,et al.  Fast CU Splitting and Pruning for Suboptimal CU Partitioning in HEVC Intra Coding , 2013, IEEE Transactions on Circuits and Systems for Video Technology.

[7]  Yung-Lyul Lee,et al.  Early Termination of CU Encoding to Reduce HEVC Complexity , 2012, IEICE Trans. Fundam. Electron. Commun. Comput. Sci..

[8]  Jianjun Lei,et al.  Early MERGE Mode Decision Based on Motion Estimation and Hierarchical Depth Correlation for HEVC , 2014, IEEE Transactions on Broadcasting.

[9]  Hao Yang,et al.  Low-Complexity CTU Partition Structure Decision and Fast Intra Mode Decision for Versatile Video Coding , 2020, IEEE Transactions on Circuits and Systems for Video Technology.

[10]  Xu Wang,et al.  Fuzzy SVM-Based Coding Unit Decision in HEVC , 2018, IEEE Transactions on Broadcasting.

[11]  Xinfeng Zhang,et al.  Fast QTBT Partitioning Decision for Interframe Coding with Convolution Neural Network , 2018, 2018 25th IEEE International Conference on Image Processing (ICIP).

[12]  Zulin Wang,et al.  Reducing Complexity of HEVC: A Deep Learning Approach , 2017, IEEE Transactions on Image Processing.

[13]  Shiqi Wang,et al.  History-Based Motion Vector Prediction for Future Video Coding , 2019, 2019 IEEE International Conference on Multimedia and Expo (ICME).

[14]  G. Bjontegaard,et al.  Calculation of Average PSNR Differences between RD-curves , 2001 .

[15]  Gary J. Sullivan,et al.  Overview of the High Efficiency Video Coding (HEVC) Standard , 2012, IEEE Transactions on Circuits and Systems for Video Technology.

[16]  Jian Zhang,et al.  Probabilistic Decision Based Block Partitioning for Future Video Coding. , 2018, IEEE transactions on image processing : a publication of the IEEE Signal Processing Society.