NDLI: Corrupted Region Restoration Using Second Order Tensors and Segmentation

Content Provider	IEEE Xplore Digital Library
Author	Jonghyun Park Nguyen Trung Kien Hyesuk Kim Gueesang Lee
Copyright Year	2007
Description	Author affiliation: Chonnam Nat. Univ., Gwangju (Jonghyun Park; Nguyen Trung Kien; Hyesuk Kim; Gueesang Lee)
Abstract	In this paper, we address the problem of restoration efficiently and effectively, by formulating as one of surface inference from a sparse and noisy point set in a 3D space. Given a set of noisy data correspondence in corrupted images, our method extracts good matches and rejects noises. The methodology is unconventional, since, unlike most other methods optimizing certain scalar, objective functions, our approach does not involve initialization or any iterative search in the parameter space. Therefore, it is free of the problem of local optima or poor convergence. Subject to the general restoration of natural images, we detect corrupted region and noises by a novel computation scheme, 3D tensor voting, which is an instance of the more general tensor voting. In essence, the input set of matches is first transformed into a sparse 3D point set. Dense, 3D tensor kernels are then used to vote for the most salient surface that captures all inliers inherent in the input. lastly, density estimation for center modes detection and separated clustering algorithm is performed later for segmentation of values according to color components in the restored image. The experimental results show that proposed approach is efficient and robust in terms of restoring and segmenting corrupted color images.
Starting Page	405
Ending Page	409
File Size	1119236
Page Count	5
File Format	PDF
ISBN	9780769528748
DOI	10.1109/FSKD.2007.231
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2007-08-24
Publisher Place	China
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Image segmentation Tensile stress Voting Impedance matching Optimization methods Image restoration Data mining Iterative methods Kernel Convergence
Content Type	Text
Resource Type	Article

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