DocumentCode
3496601
Title
An overview of inverse problem regularization using sparsity
Author
Starck, J.L. ; Fadili, M.J.
Author_Institution
Lab. AIM, Univ. Paris Diderot, Gif-sur-Yvette, France
fYear
2009
fDate
7-10 Nov. 2009
Firstpage
1453
Lastpage
1456
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.
Keywords
blind source separation; deconvolution; optimisation; blind source separation; deconvolution; inpainting; iterative thresholding methods; optimization methods; sparsity constraints; Blind source separation; Compressed sensing; Deconvolution; Dictionaries; Inverse problems; Iterative methods; Optimization methods; Sampling methods; Signal design; Wavelet transforms; Blind Source Separation; Compressed Sensing; Deconvolution; Sparsity; inpainting; iterative thresholding;
fLanguage
English
Publisher
ieee
Conference_Titel
Image Processing (ICIP), 2009 16th IEEE International Conference on
Conference_Location
Cairo
ISSN
1522-4880
Print_ISBN
978-1-4244-5653-6
Electronic_ISBN
1522-4880
Type
conf
DOI
10.1109/ICIP.2009.5414556
Filename
5414556
Link To Document