Complex Wavelet Regularization for Solving Inverse Problems in Remote Sensing

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.

• Type: Journal
• Year: 2009
• Where: IGARSS
• Authors: Mikael Carlavan, Pierre Weiss, Laure Blanc-Féraud, Josiane Zerubia
• Keywords: IGARSS 2009, Many Problems, Prior Term, Regularity Priors, Remote Sensing