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Open Access Green as soon as Postprint is submitted to ZB.
Spatially dependent regularization parameter selection in total generalized variation models for image restoration.
Int. J. Comput. Math. 90, 109-123 (2013)
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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Publication type
Article: Journal article
Document type
Scientific Article
Keywords
spatially dependent regularization parameter; total generalized variation; hierarchical decomposition; image restoration
ISSN (print) / ISBN
0020-7160
e-ISSN
1029-0265
Quellenangaben
Volume: 90,
Issue: 1,
Pages: 109-123
Publisher
Taylor & Francis
Non-patent literature
Publications
Reviewing status
Peer reviewed
Institute(s)
Institute of Computational Biology (ICB)