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Dual Block-Coordinate Forward-Backward Algorithm with Application to Deconvolution and Deinterlacing of Video Sequences

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Abstract

Optimization methods play a central role in the solution of a wide array of problems encountered in various application fields, such as signal and image processing. Especially when the problems are highly dimensional, proximal methods have shown their efficiency through their capability to deal with composite, possibly nonsmooth objective functions. The cornerstone of these approaches is the proximity operator, which has become a quite popular tool in optimization. In this work, we propose new dual forward-backward formulations for computing the proximity operator of a sum of convex functions involving linear operators. The proposed algorithms are accelerated thanks to the introduction of a block-coordinate strategy combined with a preconditioning technique. Numerical simulations emphasize the good performance of our approach for the problem of jointly deconvoluting and deinterlacing video sequences.

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Notes

  1. It is sometimes said that A is full row rank.

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Authors and Affiliations

  1. Université Paris-Est, LIGM, UMR CNRS 8049, Champs Sur Marne, France

    Feriel Abboud & Emilie Chouzenoux

  2. Center for Visual Computing, CentraleSupelec, Université Paris-Saclay, Grande Voie des Vignes, 92295, Châtenay-malabry, France

    Emilie Chouzenoux & Jean-Christophe Pesquet

  3. INA, Institut National de L’Audiovisuel, 94366, Bry Sur Marne, France

    Feriel Abboud, Jean-Hugues Chenot & Louis Laborelli

Authors
  1. Feriel Abboud
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  2. Emilie Chouzenoux
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  3. Jean-Christophe Pesquet
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  4. Jean-Hugues Chenot
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  5. Louis Laborelli
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Correspondence to Feriel Abboud.

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Abboud, F., Chouzenoux, E., Pesquet, JC. et al. Dual Block-Coordinate Forward-Backward Algorithm with Application to Deconvolution and Deinterlacing of Video Sequences. J Math Imaging Vis 59, 415–431 (2017). https://doi.org/10.1007/s10851-016-0696-y

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  • DOI: https://doi.org/10.1007/s10851-016-0696-y

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