An overview of inverse problem regularization using sparsity

Authors:
J.-L. Starck;M. J. Fadili
Affiliations:
Laboratoire AIM, UMR, CEA, DSM, CNRS, Université Paris Diderot, IRFU, SEDI-SAP, Service d'Astrophysique, Gif-Sur-Yvette cedex, France;GREYC, CNRS, ENSICAEN, Université de Caen, Caen, France
Venue:
ICIP'09 Proceedings of the 16th IEEE international conference on Image processing
Year:
2009

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Abstract

Sparsity constraints are now very popular to regularize inverse problems. We review several approaches which have been proposed in the last ten years to solve inverse problems such as inpainting, deconvolution or blind source separation. We will focus especially on optimization methods based on iterative thresholding methods to derive the solution.