Date
2006
Indexation documentaire
Probabilités et mathématiques appliquées
Subject
bandlets; Compressed sensing; best basis
Titre du colloque
NeuroComp'06
Ville du colloque
Pont-à-Mousson
Pays du colloque
FRANCE
Type
Communication / Conférence
Résumé en anglais
This paper proposes an extension of compressed sensing that allows to express the sparsity prior in a dictionary of bases. This enables the use of the universal sampling strategy of compressed sensing together with an adaptive recovery process that adapts the basis to the structure of the sensed signal. A fast greedy scheme is used during reconstruction to estimate the best basis using an iterative refinement. Numerical experiments on geometrical images show that adaptivity is indeed crucial to capture the structures of complex natural signals.