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International Conference on Scale Space and Variational Methods in Computer Vision

SSVM 2009: Scale Space and Variational Methods in Computer Vision pp 413–425Cite as

A Geometric PDE for Interpolation of M-Channel Data

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

Abstract

We propose a partial differential equation to be used for interpolating M-channel data, such as digital color images. This equation is derived via a semi-group from a variational regularization method for minimizing displacement errors. For actual image interpolation, the solution of the PDE is projected onto a space of functions satisfying interpolation constraints. A comparison of the test results with standard and state-of-the-art interpolation algorithms shows the competitiveness of this approach.

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Author information

Authors and Affiliations

  1. Department of Mathematics, University of Innsbruck, Technikerstrasse 21a, A-6020, Innsbruck, Austria

    Frank Lenzen & Otmar Scherzer

  2. Johann Radon Institute for Computational and Applied Mathematics (RICAM), Austrian Academy of Sciences, Altenbergerstrasse 69, A-4040, Linz, Austria

    Otmar Scherzer

Authors
  1. Frank Lenzen
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  2. Otmar Scherzer
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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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Lenzen, F., Scherzer, O. (2009). A Geometric PDE for Interpolation of M-Channel Data. 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_35

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  • DOI: https://doi.org/10.1007/978-3-642-02256-2_35

  • 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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