RestoMMMG_Lab : Matlab toolbox for image restoration (degradation modeled as a linear operator and a Gaussian noise)

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.
Higher Edu - Research dev card
  • Creation or important update: 28/09/11
  • Minor correction: 28/09/11
  • Index card author: Caroline Chaux (LATP)
  • Theme leader: Teresa Gomez-Diaz (LIGM)
General software features

This toolbox allows to restore an image degraded by a linear operator and Gaussian noise. The considered criterion is composed with a least square function as data fidelity term, a quadratic distance function allowing to constraint the dynamic range of the restored image into [xmin,xmax], a quadratic elastic net term allowing to ensure the existence of the solution and a regularization term favorizing piecewise constant images.
The restoration process uses the Majorize-Minimize Memory Gradient Algorithm.

Context in which the software is used

Image restoration (degradation modeled as a linear operator and a Gaussian noise).

Publications related to software
  • E. Chouzenoux, J. Idier and S. Moussaoui. A Majorize-Minimize Strategy for Subspace Optimization Applied to Image Restoration. IEEE Transactions on Image Processing, Vol. 20, No. 18, pages 1517-1528, juin 2011.
  • E. Chouzenoux, J.-C. Pesquet, H. Talbot and A. Jezierska. A Memory Gradient Algorithm for l2-l0 Regularization with Applications to Image Restoration. IEEE ICIP 2011.
  • E. Chouzenoux, Recherche de pas par Majoration-Minoration. Application à la résolution de problèmes inverses, Thèse, 2010.