Random Sensing of Geometric Images

Peyré, Gabriel

Peyré, Gabriel (2006), Random Sensing of Geometric Images, NeuroComp'06, Pont-à-Mousson, FRANCE

Type

Communication / Conférence

Date

2006

Conference title

NeuroComp'06

Conference city

Pont-à-Mousson

Conference country

FRANCE

Metadata

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Author(s)

Peyré, Gabriel

Abstract (EN)

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.

Subjects / Keywords

bandlets; Compressed sensing; best basis