File Download

There are no files associated with this item.

  • Find it @ UNIST can give you direct access to the published full text of this article. (UNISTARs only)
Related Researcher

김윤호

Kim, Yunho
Mathematical Imaging Analysis Lab.
Read More

Views & Downloads

Detailed Information

Cited time in webofscience Cited time in scopus
Metadata Downloads

Wavelet Decomposition Method for L-2/TV-Image Deblurring

Author(s)
Fornasier, M.Kim, YunhoLanger, A.Schoenlieb, C. -B.
Issued Date
2012
DOI
10.1137/100819801
URI
https://scholarworks.unist.ac.kr/handle/201301/8825
Fulltext
http://www.scopus.com/inward/record.url?partnerID=HzOxMe3b&scp=84867163734
Citation
SIAM JOURNAL ON IMAGING SCIENCES, v.5, no.3, pp.857 - 885
Abstract
In this paper, we show additional properties of the limit of a sequence produced by the subspace correction algorithm proposed by Fornasier and Schonlieb [SIAM J. Numer. Anal., 47 (2009), pp. 3397-3428 for L 2/TV-minimization problems. An important but missing property of such a limiting sequence in that paper is the convergence to a minimizer of the original minimization problem, which was obtained in [M. Fornasier, A. Langer, and C.-B. Schonlieb, Numer. Math., 116 (2010), pp. 645-685 with an additional condition of overlapping subdomains. We can now determine when the limit is indeed a minimizer of the original problem. Inspired by the work of Vonesch and Unser [IEEE Trans. Image Process., 18 (2009), pp. 509-523], we adapt and specify this algorithm to the case of an orthogonal wavelet space decomposition for deblurring problems and provide an equivalence condition to the convergence of such a limiting sequence to a minimizer. We also provide a counterexample of a limiting sequence by the algorithm that does not converge to a minimizer, which shows the necessity of our analysis of the minimizing algorithm.
Publisher
SIAM PUBLICATIONS
ISSN
1936-4954
Keyword (Author)
image deblurringwavelet decomposition methodconvex optimizationoblique thresholdingtotal variation minimizationalternating minimization
Keyword
LINEAR INVERSE PROBLEMSTOTAL VARIATION MINIMIZATIONTHRESHOLDING ALGORITHMSPARSE RECONSTRUCTIONBREGMAN ITERATIONIMAGE-RESTORATIONCONVERGENCESPACEL(1)-MINIMIZATIONREGULARIZATION

qrcode

Items in Repository are protected by copyright, with all rights reserved, unless otherwise indicated.