An Iterative Filtering Algorithm for HEVC Intra Prediction Combined with Prediction Mode Characteristics

Abstract

Nowadays, the mainstream video coding standard H.265/HEVC has achieved excellent compression performance, but it still can not match the increase of huge amount of data. In order to further optimize intra prediction of HEVC, we proposed an iterative filtering algorithm which combines the characteristics of HEVC intra prediction modes. Proposed algorithm classifies PU into different types by analyzing the characteristics of different intra prediction modes. Through discrete training methods, the coefficients of each type of filters can be obtained. And multiple iterative filtering can make the prediction more accuracy. We further optimize the complexity of the algorithm to make a balance between performance and complexity. Experimental results show that proposed algorithm can achieve better coding performance compared with HEVC baseline algorithm and some latest algorithm.