Fast CU size decision based on texture-depth relationship for depth map encoding in 3D-HEVC

Abstract

Since many advanced encoding techniques are introduced into the 3D-HEVC, it achieves higher encoding efficiency compared to HEVC. However, the encoding complexity of 3D-HEVC increases significantly when these high complexity coding techniques are used. In this paper, a new fast CU size decision algorithm based on texture-depth is proposed to reduce the depth map encoding complexity. Since there is strong correlation between texture and depth map, including motion characteristic and background region, both kinds of maps tend to choose the same CU depth as their best depth level. By building one-to-one match for collocated largest coding unit (LCU), the information of texture encoding can be used to predict the depth level of depth map. Experimental results have shown that the proposed method can achieve 41.89% time saving on average, with the negligible drop of 0.04 dB on BDPSNR and a small increase of 2.29% on BDBR.