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Proceedings Paper

Reweighted minimization algorithm for signal restoration
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Paper Abstract

In this paper, a reweighted l1 minimization algorithm for compressed sensing is proposed. The algorithm is based on generalized inverse iteration and linearized Bregman iteration, which is used for the weighted l1 minimization problem min u∈Rn {||u||ω : Au = f }. Numerical experiments confirm that the reweighted algorithm for signal restoration is effective and competitive to the recent state-of-the-art algorithms.

Paper Details

Date Published: 21 July 2017
PDF: 5 pages
Proc. SPIE 10420, Ninth International Conference on Digital Image Processing (ICDIP 2017), 104204P (21 July 2017); doi: 10.1117/12.2281703
Show Author Affiliations
Sining Huang, China Univ. of Petroleum (China)
Tiantian Qiao, China Univ. of Petroleum (China)

Published in SPIE Proceedings Vol. 10420:
Ninth International Conference on Digital Image Processing (ICDIP 2017)
Charles M. Falco; Xudong Jiang, Editor(s)

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