Fast intraprediction for high-efficiency video coding screen content coding by content analysis and dynamic thresholding

Abstract

A screen content coding (SCC) extension to high-efficiency video coding has been developed to improve the coding efficiency for videos with computer-generated text and graphics. It employs additional coding tools such as intrablock copy and palette modes for intraprediction. Although these modes can provide high coding efficiency for screen content videos, they cause an increase in computational complexity. This paper proposes a fast intraprediction algorithm for SCC by content analysis and dynamic thresholding. To skip unnecessary modes for a coding unit (CU), a rough CU classification is performed as a preprocessing step. Then, two early mode decision techniques are proposed by performing a fine-granular CU classification and deriving a content-dependent rule with adaptive thresholding based on the background color. To make early termination of CU partitions, another content-dependent rule with adaptive thresholding according to rate-distortion cost is derived to skip unnecessary partitions. In addition, a scene change detection method is adopted to update all content-dependent thresholds for different scenes in a sequence. Experimental results show that the proposed algorithm achieves 35.95% computational complexity reduction on average with 1.20% Bjøntegaard delta bitrate loss under all intraconfiguration, which outperforms all state-of-the-art algorithms in the literature.