Multiscale total variation regularization in image restoration |
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| Authors: | Yiqiu Dong Michael Hintermüller M Monserrat Rincon-Camacho |
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| Institution: | 1. Institute of Biomathematics and Biometry Helmholtz Zentrum München, Ingolstädter Landstrasse 1, 85764 Neuherberg, Germany;2. Department of Mathematics, Humboldt-University of Berlin, Unter den Linden 6, 10099 Berlin, Germany;3. START-Project "Interfaces and Free Boundaries" and SFB "Mathematical Optimization and Applications in Biomedical Science", Institute of Mathematics and Scientific Computing, University of Graz, Heinrichstrasse 36, A-8010 Graz, Austria |
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| Abstract: | A total variation model for image restoration is introduced. The model utilizes a spatially dependent regularization parameter in order to enhance image regions containing details while still sufficiently smoothing homogeneous features. A local variance estimator is used to automatically adjust the regularization parameter. A generalized hierarchical decomposition of the restored image is integrated to the algorithm in order to speed-up the performance of the update scheme. The corresponding subproblems are solved by a superlinearly convergent algorithm based on Fenchel-duality and inexact semismooth Newton techniques. Numerical tests illustrate the performance of the algorithm. (© 2011 Wiley-VCH Verlag GmbH & Co. KGaA, Weinheim) |
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