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Kim, Yunho
Mathematical Imaging Lab
Research Interests
  • Optimization, inverse problems, convex analysis, calculus of variations, partial differential equations, computational mathematics, medical/biomedical imaging

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

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Title
Wavelet Decomposition Method for L-2/TV-Image Deblurring
Author
Fornasier, M.Kim, YunhoLanger, A.Schoenlieb, C. -B.
Issue Date
2012
Publisher
SIAM PUBLICATIONS
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.
URI
https://scholarworks.unist.ac.kr/handle/201301/8825
URL
http://www.scopus.com/inward/record.url?partnerID=HzOxMe3b&scp=84867163734
DOI
10.1137/100819801
ISSN
1936-4954
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