A Novel Mode Selection-Based Fast Intra Prediction Algorithm for Spatial SHVC
Dayong Wang, Yu Sun, Weisheng Li, Lele Xie, Xin Lu, Frédéric Dufaux, Ce Zhu
Abstract
Due to multi-layer encoding and Inter-layer prediction, Spatial Scalable High-Efficiency Video Coding (SSHVC) has extremely high coding complexity. It is very crucial to improve its coding speed so as to promote widespread and cost-effective SSHVC applications. In this paper, we have proposed a novel Mode Selection-Based Fast Intra Prediction algorithm for SSHVC. We reveal the RD costs of Inter-layer Reference (ILR) mode and Intra mode have a significant difference, and the RD costs of these two modes follow Gaussian distribution. Based on this observation, we propose to apply the classic Gaussian Mixture Model and Expectation Maximization in machine learning to determine whether ILR is the best mode so as to skip the Intra mode. Experimental results demonstrate that the proposed algorithm can significantly improve the coding speed with negligible coding efficiency loss.
BibTeX
@inproceedings{icassp2023_anovelmodeselect,
title = {A Novel Mode Selection-Based Fast Intra Prediction Algorithm for Spatial SHVC},
author = {Dayong Wang and Yu Sun and Weisheng Li and Lele Xie and Xin Lu and Frédéric Dufaux and Ce Zhu},
booktitle = {ICASSP 2023},
year = {2023}
}