A Design of Fast High-Efficiency Video Coding Scheme Based on Markov Chain Monte Carlo Model and Bayesian Classifier

Abstract

The new-generation high-efficiency video coding (HEVC) standard has recently been developed by the Joint Collaborative Team on Video Coding to provide significant improvement in picture quality, especially for high-resolution videos. However, one of the most important challenges in HEVC is a high degree of computational complexity. This problem is addressed in a novel way considering skip detection and coding unit termination as two-class decision making problems. A Bayesian classifier is used for both of these approaches. Prior and class conditional probability values for a Bayesian classifier are not known at the time of encoding a video frame. Therefore, the Markov chain Monte Carlo model is used. Experimental results show that the proposed method provides significant time reduction for encoding with reasonably low loss in video quality.