Gaussian Distribution-Based Mode Selection for Intra Prediction Of Spatial SHVC

Due to the diversity of terminal devices, Spatial Scalable High Efficiency Video Coding (SSHVC) is an efficient solution to meet this requirement. However, its coding process is very complex, which seriously prevents its wide applications. Therefore, it is very crucial to reduce coding complexity and improve coding speed. In this paper, we propose a Gaussian Distribution-based Mode Selection for Intra Prediction of SSHVC. We show that the rate distortion costs of Inter-layer Reference (ILR) mode and Intra mode are significantly different, and both follow a Gaussian distribution. Based on this discovery, we propose to use a Bayes decision rule to determine whether ILR is the best mode so as to skip Intra mode. Experimental results demonstrate that the proposed algorithm can significantly improve coding speed with negligible coding efficiency losses.