Abstract : Many problems in remote sensing can be modeled as the minimization of the sum of a data term and a prior term. We propose to use a new complex wavelet based prior and an efficient scheme to solve these problems. We show some results on a problem of image reconstruction with noise, irregular sampling and blur. We also show a comparison between two widely used priors in image processing: sparsity and regularity priors.
Contributeur : Mikael Carlavan <>
Soumis le : mercredi 16 septembre 2009 - 16:14:55
Dernière modification le : vendredi 26 mars 2010 - 09:16:31
Document(s) archivé(s) le : mardi 16 octobre 2012 - 11:00:38