NDLI: Improved novel view synthesis from depth image with large baseline

Content Provider	IEEE Xplore Digital Library
Author	Chia-Ming Cheng Shu-Jyuan Lin Shang-Hong Lai Jinn-Cherng Yang
Copyright Year	2008
Description	Author affiliation: Dept. of Comput. Sci., Nat. Tsing Hua Univ., Hsinchu (Chia-Ming Cheng; Shu-Jyuan Lin; Shang-Hong Lai) \|\| Ind. Technol. Res. Inst., Hsinchu (Jinn-Cherng Yang)
Abstract	In this paper, a new algorithm is developed for recovering the large disocclusion regions in depth image based rendering (DIBR) systems on 3DTV. For the DIBR systems, undesirable artifacts occur in the disocclusion regions by using the conventional view synthesis techniques especially with large baseline. Three techniques are proposed to improve the view synthesis results. The first is the preprocessing of the depth image by using the bilateral filter, which helps to sharpen the discontinuous depth changes as well as to smooth the neighboring depth of similar color, thus restraining noises from appearing on the warped images. Secondly, on the warped image of a new viewpoint, we fill the disocclusion regions on the depth image with the background depth levels to preserve the depth structure. For the color image, we propose the depth-guided exemplar-based image inpainting that combines the structural strengths of the color gradient to preserve the image structure in the restored regions. Finally, a trilateral filter, which simultaneous combines the spatial location, the color intensity, and the depth information to determine the weighting, is applied to enhance the image synthesis results. Experimental results are shown to demonstrate the superior performance of the proposed novel view synthesis algorithm compared to the traditional methods.
Starting Page	1
Ending Page	4
File Size	754894
Page Count	4
File Format	PDF
ISBN	9781424421749
ISSN	10514651
DOI	10.1109/ICPR.2008.4761649
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2008-12-08
Publisher Place	USA
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Filters Streaming media Filtering Colored noise Image restoration Displays Filling Computer science Computer industry Rendering (computer graphics)
Content Type	Text
Resource Type	Article
Subject	Computer Vision and Pattern Recognition

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