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Title
Spatially dependent regularization parameter selection in total generalized variation models for image restoration
AuthorBredies, Kristian ; Dong, Yiqiu ; Hintermüller, Michael In der Gemeinsamen Normdatei der DNB nachschlagen
Published in
International journal of computer mathematics, London [u.a.] : Taylor and Francis, 1964 - , Vol. 90, Issue 1, page 109-123
PublishedTaylor & Francis
Edition
Accepted version
LanguageEnglish
Document typeJournal Article
Keywords (EN)spatially dependent regularization Parameter / total generalized variation / hierarchical decomposition / image restoration
ISSN1029-0265
URNurn:nbn:at:at-ubg:3-323 Persistent Identifier (URN)
DOIdoi:10.1080/00207160.2012.700400 
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 The work is publicly available
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Spatially dependent regularization parameter selection in total generalized variation models for image restoration [3.06 mb]
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Abstract (English)

In this paper, the automated spatially dependent regularization parameter selection framework for multi-scale image restoration is applied to total generalized variation (TGV) of order 2. Well-posedness of the underlying continuous models is discussed and an algorithm for the numerical solution is developed. Experiments confirm that due to the spatially adapted regularization parameter, the method allows for a faithful and simultaneous recovery of fine structures and smooth regions in images. Moreover, because of the TGV regularization term, the adverse staircasing effect, which is a well-known drawback of the total variation regularization, is avoided.

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