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Titel
Spatially dependent regularization parameter selection in total generalized variation models for image restoration
VerfasserBredies, Kristian ; Dong, Yiqiu ; Hintermüller, Michael In der Gemeinsamen Normdatei der DNB nachschlagen
Erschienen in
International journal of computer mathematics, London [u.a.] : Taylor and Francis, 1.1964/65 -, Jg. 90, H. 1, S. 109-123
ErschienenTaylor & Francis
SpracheEnglisch
DokumenttypAufsatz in einer Zeitschrift
Schlagwörter (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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Spatially dependent regularization parameter selection in total generalized variation models for image restoration [3.06 mb]
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Zusammenfassung (Englisch)

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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