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

Authors: Liming Chen; Zhaoqing Pan; Xiaokai Yi; Yajuan Zhang

Addresses: School of Computer and Software, Nanjing University of Information Science and Technology, Nanjing 210044, China ' School of Computer and Software, Jiangsu Collaborative Innovation Centre on Atmospheric Environment and Equipment Technology, Nanjing University of Information Science and Technology, Nanjing 210044, China ' School of Computer and Software, Nanjing University of Information Science and Technology, Nanjing 210044, China ' School of Computer Science and Engineering, Hebei University of Technology, Tianjin 300401, China

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.

Keywords: 3D-HEVC; early termination; CU split; PU mode; depth map.

DOI: 10.1504/IJCSE.2019.103957

International Journal of Computational Science and Engineering, 2019 Vol.20 No.3, pp.345 - 353

Received: 21 Aug 2017
Accepted: 24 Jan 2018
Published online: 03 Dec 2019 *

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