Numerical Methods and Applications in Total Variation Image Restoration

Raymond Chan (), Tony F. Chan () and Andy Yip ()
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Raymond Chan: The Chinese University of Hong Kong, Department of Mathematics
Tony F. Chan: Hong Kong University of Science and Technology, Office of the President
Andy Yip: Hong Kong Baptist University, Department of Mathematics

A chapter in Handbook of Mathematical Methods in Imaging, 2015, pp 1501-1537 from Springer

Abstract: Abstract Since their introduction in a classic paper by Rudin, Osher, and Fatemi (Physica D 60:259–268, 1992), total variation minimizing models have become one of the most popular and successful methodologies for image restoration. New developments continue to expand the capability of the basic method in various aspects. Many faster numerical algorithms and more sophisticated applications have been proposed. This chapter reviews some of these recent developments.

Keywords: Augmented Lagrangian Method; Total Variation Minimization; Bregman Iteration; Total Variation Denoising; Split Bregman Iteration (search for similar items in EconPapers)
Date: 2015
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DOI: 10.1007/978-1-4939-0790-8_24

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