Fast Intra Prediction Based on Content Property Analysis for Low Complexity HEVC-Based Screen Content Coding

TLDR: Experimental results show that the proposed algorithm can save 44.92% encoding time on average with negligible loss of video quality.

Abstract: Screen content coding (SCC) has evolved into the extension of the High Efficiency Video Coding (HEVC). Low-latency, real-time transport between devices in the form of screen content video is becoming popular in many applications. However, the complexity of encoder is still very high for intra prediction in HEVC-based SCC. This paper proposes a fast intra prediction method based on content property analysis for HEVC-based SCC. First, coding units (CUs) are classified into natural content CUs (NCCUs) and screen content CUs (SCCUs), based on the statistic characteristics of the content. For NCCUs, the newly adopted prediction modes, including intra block copy mode and palette mode are skipped, if the DC or PLANR mode is the best mode, after testing the traditional intra prediction rough modes. In addition, the quadtree partition process is also terminated due to the homogeneous and smooth block usually chooses a large size CU. For SCCUs, a rank-based decision strategy is introduced to terminate the splitting process of current CU. For all CUs, the bit per pixel of current CU is used to make a CU size decision. Meanwhile, the depth information of neighboring CUs and co-located CU are utilized to further improve the performance. Experimental results show that the proposed algorithm can save 44.92% encoding time on average with negligible loss of video quality.