21 July 2017 Reweighted minimization algorithm for signal restoration
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Proceedings Volume 10420, Ninth International Conference on Digital Image Processing (ICDIP 2017); 104204P (2017) https://doi.org/10.1117/12.2281703
Event: Ninth International Conference on Digital Image Processing (ICDIP 2017), 2017, Hong Kong, China
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.
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Sining Huang, Sining Huang, Tiantian Qiao, Tiantian Qiao, } "Reweighted minimization algorithm for signal restoration", Proc. SPIE 10420, Ninth International Conference on Digital Image Processing (ICDIP 2017), 104204P (21 July 2017); doi: 10.1117/12.2281703; https://doi.org/10.1117/12.2281703
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