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An efficient depth map filtering based on spatial and texture features for 3D video coding

delete2016-05-01
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PRE
AI
Q
Qiuwen Zhang *
M
Ming Chen
H
Haodong Zhu
王
王小兵 (Xiaobing Wang)
Y
Yong Gan
DOI:10.1016/j.neucom.2014.11.103delete
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Abstract

Abstract

En 中文
A depth map is used to synthesize virtual views in the 3D video depth-enhanced format. In contrast to texture video, depth map is characterized by piecewise smooth regions bounded by sharp object boundaries. Conventional video coding standards compress depth map often introduces coding artifacts along the depth map boundary, which severely affects the rendered view quality. To address this problem, we propose an efficient depth map filtering for 3D depth map compression in the high efficiency video coding (HEVC) process. The proposed depth map filtering is designed considering spatial resolution, texture boundary similarity, and coding artifacts features. It consists of a newly designed nonlinear down/up sampling filtering and a depth reconstruction multilateral filtering. Firstly, the depth map is down-sampled and coded with 3D video HEVC. Then in the decoding side, the depth map is up-sampled. Finally, a depth reconstruction multilateral filtering is used to align the object boundaries for the coding artifacts in edges of the decoded depth image. Experimental results demonstrate that the proposed depth map filtering can significantly reduce the bit rate as well as achieving a better quality of the rendered view in comparison with 3D video HEVC test model (3DV-HTM). (C) 2015 Elsevier B.V. All rights reserved.
Keywords:
3D video
Depth map
High-efficiency video coding (HEVC)
Virtual views
Spatial and texture features
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Journal

Neurocomputing cover
Neurocomputing
IF:
6.5
Papers:
2.5W
Citations:
6.5W

Organization

Z
Zhengzhou University of Light Industry
Scholars:
6.4K
Papers: 4.0K
Citations: 5.4K
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