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Non-local Regularization of Inverse Problems

  • Gabriel Peyré
  • Sébastien Bougleux
  • Laurent Cohen
Part of the Lecture Notes in Computer Science book series (LNCS, volume 5304)

Abstract

This article proposes a new framework to regularize linear inverse problems using the total variation on non-local graphs. This non-local graph allows to adapt the penalization to the geometry of the underlying function to recover. A fast algorithm computes iteratively both the solution of the regularization process and the non-local graph adapted to this solution. We show numerical applications of this method to the resolution of image processing inverse problems such as inpainting, super-resolution and compressive sampling.

Keywords

Inverse Problem Compressive Sampling Graph Regularization Image Inpainting Proximity Operator 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

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Copyright information

© Springer-Verlag Berlin Heidelberg 2008

Authors and Affiliations

  • Gabriel Peyré
    • 1
  • Sébastien Bougleux
    • 1
  • Laurent Cohen
    • 1
  1. 1.Université Paris-Dauphine, CEREMADEParis Cedex 16France

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