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Deinterlacing with Motion-Compensated Anisotropic Diffusion

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Statistical and Geometrical Approaches to Visual Motion Analysis

Part of the book series: Lecture Notes in Computer Science ((LNIP,volume 5604))

Abstract

We present a novel deinterlacing scheme that makes consequent use of discontinuity-preserving partial differential equations (PDEs). It combines the accuracy of recent variational motion estimation techniques with the directional interpolation qualities of anisotropic diffusion filters. Our algorithm proceeds in three steps: First, we interpolate the interlaced images by means of a spatial edge enhancing diffusion process (EED). Then we apply the variational optic flow technique of Brox et al. (2004) in order to obtain a precise interframe registration. Finally we use a spatiotemporal generalisation of EED for motion-compensated inpainting of the missing data in the original sequence. Experiments demonstrate that the proposed method outperforms not only classical deinterlacing schemes, but also a recent PDE-based approach.

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Authors and Affiliations

  1. Mathematical Image Analysis Group, Faculty of Mathematics and Computer Science, Saarland University, Building E1.1, 66041, Saarbrücken, Germany

    Matthias Ghodstinat, Andrés Bruhn & Joachim Weickert

Authors
  1. Matthias Ghodstinat
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  2. Andrés Bruhn
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  3. Joachim Weickert
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Editor information

Editors and Affiliations

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

    Daniel Cremers  & Frank R. Schmidt  & 

  2. Institut für Informationsverarbeitung, Leibniz Universität Hannover, Appelstraße 9A, 30167, Hannover, Germany

    Bodo Rosenhahn

  3. Department of Statistics and Psychology, University of California - Los Angeles, 8967 Math Sciences Building, 90095-1554, Los Angeles, CA, USA

    Alan L. Yuille

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Ghodstinat, M., Bruhn, A., Weickert, J. (2009). Deinterlacing with Motion-Compensated Anisotropic Diffusion. In: Cremers, D., Rosenhahn, B., Yuille, A.L., Schmidt, F.R. (eds) Statistical and Geometrical Approaches to Visual Motion Analysis. Lecture Notes in Computer Science, vol 5604. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-03061-1_5

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  • DOI: https://doi.org/10.1007/978-3-642-03061-1_5

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-642-03060-4

  • Online ISBN: 978-3-642-03061-1

  • eBook Packages: Computer ScienceComputer Science (R0)

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