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Regularization Parameter Selection in Total Variation Based Image Denoising
Author(s) -
Dong Yiqiu,
Hintermüller Michael,
Rincon Monserrat
Publication year - 2008
Publication title -
pamm
Language(s) - English
Resource type - Journals
ISSN - 1617-7061
DOI - 10.1002/pamm.200810931
Subject(s) - total variation denoising , regularization (linguistics) , image denoising , noise reduction , mathematical optimization , mathematics , selection (genetic algorithm) , algorithm , variation (astronomy) , computer science , artificial intelligence , physics , astrophysics
A new approach of selecting the regularization parameter in a multiscale total variation model is proposed. The method is combined with a primal–dual algorithm to get a new iteration method for noise removal. Numerical results illustrate significant improvement over other popular methods. (© 2008 WILEY‐VCH Verlag GmbH & Co. KGaA, Weinheim)