NDLI: Image reconstruction by linear programming

Content Provider	IEEE Xplore Digital Library
Author	Tsuda, K. Ratsch, G.
Copyright Year	1992
Abstract	One way of image denoising is to project a noisy image to the subspace of admissible images derived, for instance, by PCA. However, a major drawback of this method is that all pixels are updated by the projection, even when only a few pixels are corrupted by noise or occlusion. We propose a new method to identify the noisy pixels by /spl lscr//sub 1/-norm penalization and to update the identified pixels only. The identification and updating of noisy pixels are formulated as one linear program which can be efficiently solved. In particular, one can apply the /spl nu/ trick to directly specify the fraction of pixels to be reconstructed. Moreover, we extend the linear program to be able to exploit prior knowledge that occlusions often appear in contiguous blocks (e.g., sunglasses on faces). The basic idea is to penalize boundary points and interior points of the occluded area differently. We are also able to show the /spl nu/ property for this extended LP leading to a method which is easy to use. Experimental results demonstrate the power of our approach.
Sponsorship	IEEE Signal Processing Society
Page Count	8
File Size	604256
Starting Page	737
Ending Page	744
File Format	PDF
ISSN	10577149
Volume Number	14
Issue Number	6
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2005-06-01
Publisher Place	U.S.A.
Access Restriction	One Nation One Subscription (ONOS)
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Image reconstruction Linear programming Principal component analysis Noise robustness Noise reduction Image denoising Cybernetics Image restoration Smoothing methods Kernel robust projection image reconstruction linear programming occlusion detection
Content Type	Text
Resource Type	Article
Subject	Computer Graphics and Computer-Aided Design Software

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