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Adaptive depth truncation filter for MVC based compressed depth image

delete2014-03-01
delete10
PRE
AI
X
Xuyuan Xu *
L
Lai-Man Po
T
Terence Cheung
W
William K. Cheung
L
Litong Feng
DOI:10.1016/j.image.2013.12.005delete
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摘要

摘要

En 中文
In multiview video plus depth (MVD) format, virtual views are generated from decoded texture videos with corresponding decoded depth images through depth image based rendering (DIBR). 3DV-ATM is a reference model for the H.264/AVC based multiview video coding (MVC) and aims at achieving high coding efficiency for 3D video in MVD format. Depth images are first downsampled then coded by 3DV-ATM. However, sharp object boundary characteristic of depth images does not well match with the transform coding based nature of H.264/AVC in 3DV-ATM. Depth boundaries are often blurred with ringing artifacts in the decoded depth images that result in noticeable artifacts in synthesized virtual views. This paper presents a low complexity adaptive depth truncation filter to recover the sharp object boundaries of the depth images using adaptive block repositioning and expansion for increasing the depth values refinement accuracy. This new approach is very efficient and can avoid false depth boundary refinement when block boundaries lie around the depth edge regions and ensure sufficient information within the processing block for depth layers classification. Experimental results demonstrate that the sharp depth edges can be recovered using the proposed filter and boundary artifacts in the synthesized views can be removed. The proposed method can provide improvement up to 325 dB in the depth map enhancement and bitrate reduction of 3.06% in the synthesized views. (C) 2014 Elsevier B.V. All rights reserved.
Keyword:
Multiview video plus depth (MVD)
Depth image based rendering (DIBR)
3DV-ATM
Multiview video coding (MVC)
Depth image compression
Depth image filter

期刊

S
Signal Processing and Image Communication
IF:
2.7
论文数:
2.8K
被引数:
4.2K

机构

Hong Kong Chu Hai College 封面图
Hong Kong Chu Hai College
学者数:
82
论文数: 85
被引数: 65
C
City University of Hong Kong
学者数:
2.3W
论文数: 3.0W
被引数: 6.1W
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