Reweighted minimization algorithm for signal restoration

Sining Huang; Tiantian Qiao

doi:10.1117/12.2281703

21 July 2017 Reweighted minimization algorithm for signal restoration

Sining Huang, Tiantian Qiao

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.

Citation Download Citation

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

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