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Numerical Methods and Applications in Total Variation Image Restoration

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Handbook of Mathematical Methods in Imaging

Abstract

Since their introduction in a classic paper by Rudin, Osher, and Fatemi [51],total variation minimizing models have become one of the most popular andsuccessful methodologies for image restoration. New developments continue toexpand the capability of the basic method in various aspects. Many fasternumerical algorithms and more sophisticated applications have been proposed.This chapter reviews some of these recent developments.

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Author information

Authors and Affiliations

  1. The Chinese University of Hong Kong, Shatin, Hong Kong

    Raymond Chan

  2. University of California Los Angeles, Los Angeles, CA, USA

    Tony Chan

  3. National University of Singapore, Singapore, Singapore

    Andy Yip

Authors
  1. Raymond Chan
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  2. Tony Chan
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  3. Andy Yip
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Editor information

Editors and Affiliations

  1. Computational Science Center, University of Vienna, Nordbergstrasse 15, Vienna, Austria

    Otmar Scherzer

  2. RICAM, Austrian Academy of Sciences, Linz, Austria

    Otmar Scherzer

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Chan, R., Chan, T., Yip, A. (2011). Numerical Methods and Applications in Total Variation Image Restoration. In: Scherzer, O. (eds) Handbook of Mathematical Methods in Imaging. Springer, New York, NY. https://doi.org/10.1007/978-0-387-92920-0_24

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