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Proceedings Paper • Open Access

A wide-angle view at iterated shrinkage algorithms
Author(s): M. Elad; B. Matalon; J. Shtok; M. Zibulevsky

Paper Abstract

Sparse and redundant representations − an emerging and powerful model for signals − suggests that a data source could be described as a linear combination of few atoms from a pre-specified and over-complete dictionary. This model has drawn a considerable attention in the past decade, due to its appealing theoretical foundations, and promising practical results it leads to. Many of the applications that use this model are formulated as a mixture of l2-lp (p ≤ 1) optimization expressions. Iterated Shrinkage algorithms are a new family of highly effective numerical techniques for handling these optimization tasks, surpassing traditional optimization techniques. In this paper we aim to give a broad view of this group of methods, motivate their need, present their derivation, show their comparative performance, and most important of all, discuss their potential in various applications.

Paper Details

Date Published: 13 September 2007
PDF: 19 pages
Proc. SPIE 6701, Wavelets XII, 670102 (13 September 2007); doi: 10.1117/12.741299
Show Author Affiliations
M. Elad, The Technion-Israel Institute of Technology (Israel)
B. Matalon, The Technion-Israel Institute of Technology (Israel)
J. Shtok, The Technion-Israel Institute of Technology (Israel)
M. Zibulevsky, The Technion-Israel Institute of Technology (Israel)

Published in SPIE Proceedings Vol. 6701:
Wavelets XII
Dimitri Van De Ville; Vivek K. Goyal; Manos Papadakis, Editor(s)

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