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International Conference on Scale Space and Variational Methods in Computer Vision

SSVM 2013: Scale Space and Variational Methods in Computer Vision pp 24–35Cite as

Expert Regularizers for Task Specific Processing

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Part of the book series: Lecture Notes in Computer Science ((LNIP,volume 7893))

Abstract

This study is concerned with constructing expert regularizers for specific tasks. We discuss the general problem of what is desired from a regularizer, when one knows the type of images to be processed. The aim is to improve the processing quality and to reduce artifacts created by standard, general-purpose, regularizers, such as total-variation or nonlocal functionals.

Fundamental requirements for the theoretic expert regularizer are formulated. A simplistic regularizer is then presented, which approximates in some sense the ideal requirements.

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Author information

Authors and Affiliations

  1. Department of Electrical Engineering, Technion, Israel Institute of Technology, Haifa, 32000, Israel

    Guy Gilboa

Authors
  1. Guy Gilboa
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Editor information

Editors and Affiliations

  1. Fraunhofer Gesellschaft, Institut für Graphische Datenverarbeitung, Fraunhoferstraße 5, 64283, Darmstadt, Germany

    Arjan Kuijper

  2. Institute for Mathematics and Scientific Computing, University of Graz, Heinrichstrasse 36, 8010, Graz, Austria

    Kristian Bredies

  3. Institute for Computer Graphics and Vision, Graz University of Technology, Inffeldgasse 16, 8010, Graz, Austria

    Thomas Pock  & Horst Bischof  & 

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Gilboa, G. (2013). Expert Regularizers for Task Specific Processing. In: Kuijper, A., Bredies, K., Pock, T., Bischof, H. (eds) Scale Space and Variational Methods in Computer Vision. SSVM 2013. Lecture Notes in Computer Science, vol 7893. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-38267-3_3

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  • DOI: https://doi.org/10.1007/978-3-642-38267-3_3

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-642-38266-6

  • Online ISBN: 978-3-642-38267-3

  • eBook Packages: Computer ScienceComputer Science (R0)

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