Adaptive CU split prediction and fast mode decision for 3D-HEVC texture coding based on just noticeable difference model

Abstract

3D-high efficiency video coding (3D-HEVC) is the latest extension of HEVC standard. Through adopting novel coding tools, 3D-HEVC could improve the compression efficiency of multi-view texture video. However, with the great bitrate savings, 3D-HEVC brings the extreme complexity. To reduce the encoding time of texture video, a fast 3D-HEVC method based on just noticeable difference (JND) model is proposed in this paper. The JND model is introduced to analyze the coding tree block (CTB) characteristics of the texture image. Moreover, combining with adaptive coding unit (CU) split prediction and fast mode decision, the proposed scheme could skip some CTBs of texture video at the early stage without a normal coding procedure. Simulation results demonstrate that the proposed scheme can reduce 51.5% encoding runtime on average with negligible loss of subjective quality.