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International Workshop on Energy Minimization Methods in Computer Vision and Pattern Recognition

EMMCVPR 2009: Energy Minimization Methods in Computer Vision and Pattern Recognition pp 112–125Cite as

A PDE Approach to Coupled Super-Resolution with Non-parametric Motion

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Part of the book series: Lecture Notes in Computer Science ((LNIP,volume 5681))

Abstract

The problem of recovering a high-resolution image from a set of distorted (e.g., warped, blurred, noisy) and low-resolution images is known as super-resolution. Accurate motion estimation among the low-resolution measurements is a fundamental challenge of the super-resolution problem. Some recent promising advances in this area have been focused on coupling or combing the super-resolution reconstruction and the motion estimation. However, the existing approach is limited to parametric motion models, e.g., affine. In this paper, we shall address the coupled super-resolution problem with a non-parametric motion model. We address the problem in a variational formulation and propose a PDE-approach to yield a numerical scheme. In this approach, we use diffusion regularizations for both the motion and the super-resolved image. However, the approach is flexible and other suitable regularization schemes may be employed in the proposed formulation.

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Author information

Authors and Affiliations

  1. Department of Medical Biophysics, University of Toronto Imaging Research, Sunnybrook Health Sciences Centre, Toronto, Ontario, Canada

    Mehran Ebrahimi & Anne L. Martel

Authors
  1. Mehran Ebrahimi
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  2. Anne L. Martel
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Editor information

Editors and Affiliations

  1. Institut für Informatik III, Rö, Universität Bonn, merstraße 164, 53117, Bonn, Germany

    Daniel Cremers

  2. Computer Science Department, University of Western Ontario, N6A 5A5, London, ON, Canada

    Yuri Boykov

  3. Microsoft Research, J.J. Thomson Avenue, CB3 OFB, Cambridge, United Kingdom

    Andrew Blake

  4. Institut für Informatik III, Universität Bonn, Römerstraße 164, 53117, Bonn, Germany

    Frank R. Schmidt

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© 2009 Springer-Verlag Berlin Heidelberg

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Ebrahimi, M., Martel, A.L. (2009). A PDE Approach to Coupled Super-Resolution with Non-parametric Motion. In: Cremers, D., Boykov, Y., Blake, A., Schmidt, F.R. (eds) Energy Minimization Methods in Computer Vision and Pattern Recognition. EMMCVPR 2009. Lecture Notes in Computer Science, vol 5681. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-03641-5_9

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  • DOI: https://doi.org/10.1007/978-3-642-03641-5_9

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-642-03640-8

  • Online ISBN: 978-3-642-03641-5

  • eBook Packages: Computer ScienceComputer Science (R0)

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