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Received: 2008-11-20

Revision Accepted: 2009-01-04

Crosschecked: 2009-10-18

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Journal of Zhejiang University SCIENCE A 2009 Vol.10 No.12 P.1738~1749


Depth-aided inpainting for disocclusion restoration of multi-view images using depth-image-based rendering

Author(s):  Kai LUO, Dong-xiao LI, Ya-mei FENG, Ming ZHANG

Affiliation(s):  Department of Information Science and Electronic Engineering, Zhejiang University, Hangzhou 310027, China

Corresponding email(s):   luokai82@gmail.com, lidx@zju.edu.cn

Key Words:  Depth-aided inpainting, Disocclusion restoration, Depth-image-based rendering (DIBR), Image warping, Stereoscopic image, Multi-view image, 3D-TV

Kai LUO, Dong-xiao LI, Ya-mei FENG, Ming ZHANG. Depth-aided inpainting for disocclusion restoration of multi-view images using depth-image-based rendering[J]. Journal of Zhejiang University Science A, 2009, 10(12): 1738~1749.

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publisher="Zhejiang University Press & Springer",

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%T Depth-aided inpainting for disocclusion restoration of multi-view images using depth-image-based rendering
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%A Ya-mei FENG
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%I Zhejiang University Press & Springer
%DOI 10.1631/jzus.A0820806

T1 - Depth-aided inpainting for disocclusion restoration of multi-view images using depth-image-based rendering
A1 - Kai LUO
A1 - Dong-xiao LI
A1 - Ya-mei FENG
A1 - Ming ZHANG
J0 - Journal of Zhejiang University Science A
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SP - 1738
EP - 1749
%@ 1673-565X
Y1 - 2009
PB - Zhejiang University Press & Springer
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DOI - 10.1631/jzus.A0820806

A new algorithm is proposed for restoring disocclusion regions in depth-image-based rendering (DIBR) warped images. Current solutions include layered depth image (LDI), pre-filtering methods, and post-processing methods. The LDI is complicated, and pre-filtering of depth images causes noticeable geometrical distortions in cases of large baseline warping. This paper presents a depth-aided inpainting method which inherits merits from Criminisi’s inpainting algorithm. The proposed method features incorporation of a depth cue into texture estimation. The algorithm efficiently handles depth ambiguity by penalizing larger Lagrange multipliers of filling points closer to the warping position compared with the surrounding existing points. We perform morphological operations on depth images to accelerate the algorithm convergence, and adopt a luma-first strategy to adapt to various color sampling formats. Experiments on test multi-view sequence showed that our method has superiority in depth differentiation and geometrical loyalty in the restoration of warped images. Also, peak signal-to-noise ratio (PSNR) statistics on non-hole regions and whole image comparisons both compare favorably to those obtained by state of the art techniques.

Darkslateblue:Affiliate; Royal Blue:Author; Turquoise:Article


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