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Multi-scale Total Variation with Automated Regularization Parameter Selection for Color Image Restoration

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Scale Space and Variational Methods in Computer Vision (SSVM 2009)

Part of the book series: Lecture Notes in Computer Science ((LNIP,volume 5567))

Abstract

In this paper, a multi-scale vectorial total variation model for color image restoration is introduced. The model utilizes a spatially dependent regularization parameter in order to preserve the details during noise removal. The automated adjustment strategy of the regularization parameter is based on local variance estimators combined with a confidence interval technique. Numerical results on images are presented to demonstrate the efficiency of the method.

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Author information

Authors and Affiliations

  1. 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

    Yiqiu Dong

  2. Department of Mathematics, Humboldt-University of Berlin, Unter den Linden 6, 10099 Berlin, Germany, 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

    Michael Hintermüller

Authors
  1. Yiqiu Dong
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  2. Michael Hintermüller
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Editor information

Editors and Affiliations

  1. Department of Mathematics, University of Bergen, Johannes Brunsgate 12, 5008, Bergen, Norway

    Xue-Cheng Tai

  2. Department of Informatics and Centre of Mathematics for Applications, University of Oslo, Oslo, Norway

    Knut Mørken

  3. Simula Research Laboratory, M. Linges v 17, Fornebu, P.O.Box 134, N-1325, Lysaker, Norway

    Marius Lysaker

  4. SINTEF ICT, Oslo, Norway

    Knut-Andreas Lie

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© 2009 Springer-Verlag Berlin Heidelberg

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Dong, Y., Hintermüller, M. (2009). Multi-scale Total Variation with Automated Regularization Parameter Selection for Color Image Restoration. In: Tai, XC., Mørken, K., Lysaker, M., Lie, KA. (eds) Scale Space and Variational Methods in Computer Vision. SSVM 2009. Lecture Notes in Computer Science, vol 5567. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-02256-2_23

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  • DOI: https://doi.org/10.1007/978-3-642-02256-2_23

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-642-02255-5

  • Online ISBN: 978-3-642-02256-2

  • eBook Packages: Computer ScienceComputer Science (R0)

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