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Field of Particle Filters for Image Inpainting

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Abstract

We present a novel algorithm for solving the image inpainting problem based on a field of locally interacting particle filters. Image inpainting, also known as image completion, is concerned with the problem of filling image regions with new visually plausible data. In order to avoid the difficulty of solving the problem globally for the region to be inpainted, we introduce a field of local particle filters. The states of the particle filters are image patches. Global consistency is enforced by a Markov random field image model which connects neighbouring particle filters. The benefit of using locally interacting particle filters is that several competing hypotheses on inpainting solutions are kept active, allowing the method to provide globally consistent solutions on problems where other local methods may fail. We provide examples of applications of the developed method.

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Authors and Affiliations

  1. Lab-STICC, European University of Brittany, Vannes, France

    Anne Cuzol

  2. Department of Computer Science, University of Copenhagen, Copenhagen, Denmark

    Anne Cuzol, Kim Steenstrup Pedersen & Mads Nielsen

  3. Nordic Bioscience A/S, Herlev, Denmark

    Mads Nielsen

Authors
  1. Anne Cuzol
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  2. Kim Steenstrup Pedersen
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  3. Mads Nielsen
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Correspondence to Anne Cuzol.

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Cuzol, A., Pedersen, K.S. & Nielsen, M. Field of Particle Filters for Image Inpainting. J Math Imaging Vis 31, 147–156 (2008). https://doi.org/10.1007/s10851-008-0072-7

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  • DOI: https://doi.org/10.1007/s10851-008-0072-7

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