Higher Edu - Research dev card
Development from the higher education and research community
  • Creation or important update: 04/03/11
  • Minor correction: 25/03/11

TexGeoPPXA_Lab : Matlab toolbox for geometry/texture decomposition

This software was developed (or is under development) within the higher education and research community. Its stability can vary (see fields below) and its working state is not guaranteed.
  • Web site
  • System: UNIX-like, Windows, MacOS X
  • Current version: v1.0 - octobre 2010
  • License(s): CeCILL-B
  • Status: stable release
  • Support: maintained, no ongoing development
  • Designer(s): Nelly Pustelnik
  • Contact designer(s): nelly.pustelnik_@_ims-bordeaux.fr
  • Laboratory, service: LIGM


General software features

This software performs geometry/texture decomposition from a degraded observation. By degradation we mean convolution operator and Poisson noise.
The method is based on convex criterion minimization. The criterion contains 4 terms :

  • Kullback-Leibler divergence
  • indicator function
  • l1 norm applied on frame coefficients (texture component)
  • total variation applied on geometry component

The PPXA (Parallel ProXimal Algorithm) is used to perform the minimization.

Context in which the software is used

This software performs geometry/texture decomposition from a degraded (convolution + Poisson noise) observation.

Publications related to the software
  • N. Pustelnik, M√©thodes proximales pour la r√©solution de probl√®mes inverses. Application √† la Tomographie par Emission de Positrons. Th√®se Universit√© Paris-Est, 2010.
  • L. M. Briceno-Arias, P. L. Combettes, J.-C. Pesquet, and N. Pustelnik, Proximal method for geometry and texture image decomposition, International Conference on Image Processing (ICIP) , Honk Kong, 26-29 Septembre 2010.
  • http://nellypustelnik.perso.sfr.fr/