Journal of Mathematical Imaging and Vision

, Volume 47, Issue 3, pp 167–178 | Cite as

A Parallel Proximal Splitting Method for Disparity Estimation from Multicomponent Images Under Illumination Variation

  • C. ChauxEmail author
  • M. El-Gheche
  • J. Farah
  • J.-C. Pesquet
  • B. Pesquet-Popescu


Proximal splitting algorithms play a central role in finding the numerical solution of convex optimization problems. This paper addresses the problem of stereo matching of multi-component images by jointly estimating the disparity and the illumination variation. The global formulation being non-convex, the problem is addressed by solving a sequence of convex relaxations. Each convex relaxation is non trivial and involves many constraints aiming at imposing some regularity on the solution. Experiments demonstrate that the method is efficient and provides better results compared with other approaches.


Stereo Disparity Color images Illumination variation Proximity operator Total variation Tight frame Convex optimization Parallel proximal algorithms 



We would like to thank Prof. Wided Miled for providing us with her codes. We would also like to thank Dr. Raffaele Gaetano and Giovanni Chierchia for their implementation of our approach on GPU architectures.


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Copyright information

© Springer Science+Business Media, LLC 2012

Authors and Affiliations

  • C. Chaux
    • 1
    Email author
  • M. El-Gheche
    • 1
  • J. Farah
    • 2
  • J.-C. Pesquet
    • 1
  • B. Pesquet-Popescu
    • 3
  1. 1.Laboratoire d’Informatique Gaspard Monge—CNRS UMR 8049Université Paris-EstMarne la Vallée Cedex 2France
  2. 2.Department of Telecommunications, Faculty of EngineeringHoly-Spirit University of KaslikJouniehLebanon
  3. 3.Signal and Image Proc. Dept.Telecom ParisTechParisFrance

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