Learning-Based Complexity Reduction Scheme for VVC Intra-Frame Prediction
Mário Saldanha, Gustavo Sanchez, Cesar Augusto Missio Marcon, Luciano Volcan Agostini · 2021 International Conference on Visual Communications and Image Processing (VCIP) · 2021
This paper presents a learning-based complexity reduction scheme for Versatile Video Coding (VVC) intra-frame prediction. VVC introduces several novel coding tools to improve the coding efficiency of the intra-frame prediction at the cost of a high computational effort. Thus, we developed an efficient complexity reduction scheme composed of three solutions based on machine learning and statistical analysis to reduce the number of intra prediction modes evaluated in the costly Rate-Distortion Optimization (RDO) process. Experimental results demonstrated that the proposed solution provides 18.32% encoding timesaving with a negligible impact on the coding efficiency.