Paper
29 October 2014 Joint bit allocation for 3D video coding based on virtual view distortion
Author Affiliations +
Abstract
In multi-view plus depth (MVD) 3D video coding, texture maps and depth maps are coded jointly. The depth maps provide the scene geometry information and are used to render the virtual view at the terminal through a Depth-Image-Based-Rendering (DIBR) technique. The distortion of the coded texture maps and depth maps will induce synthesized virtual view distortion. Besides the coding efficiency of texture maps and depth maps, bit allocation between texture maps and depth maps also has a great effect on the virtual view quality. In this paper, the virtual view distortion is divided into texture maps induced distortion and depth maps induced distortion separately, models of texture maps induced virtual view distortion and depth maps induced virtual view distortion are derived respectively. Based on the depth maps induced virtual view distortion model, depth maps coding Rate Distortion Optimization (RDO) is modified and the depth maps coding efficiency is increased. Meanwhile, we also propose a Rate-distortion (R-D) model to solve the joint bit allocation problem. Experimental results demonstrate the high accuracy of the proposed virtual view distortion model. The R-D performance of the proposed algorithm is close to the full search algorithm that can give the best R-D performance, while the coding complexity of the proposed algorithm is lower. Compared with fixed texture and depth bits ratio (5:1), an average 0.3 dB gains can be achieved by the proposed algorithm. The proposed algorithm has high rate control accuracy with the average error less than 1%.
© (2014) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.
Chao Yang, Ping An, Jianxin Wang, and Zhaoyang Zhang "Joint bit allocation for 3D video coding based on virtual view distortion", Proc. SPIE 9273, Optoelectronic Imaging and Multimedia Technology III, 92730N (29 October 2014); https://doi.org/10.1117/12.2070924
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Cited by 2 scholarly publications.
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KEYWORDS
Distortion

Volume rendering

Image compression

Video coding

Quantization

3D video compression

Video

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