A FAST ITERATIVE SHRINKAGE-THRESHOLDING ALGORITHM WITH APPLICATION TO WAVELET-BASED IMAGE DEBLURRING

被引：175

作者：

Beck, Amir ^{[1
]}

Teboulle, Marc ^{[2
]}

机构：

[1] Technion Israel Inst Technol, Fac Ind Engn & Management, IL-32000 Haifa, Israel

[2] Tel Aviv Univ, Sch Math Sci, IL-69978 Tel Aviv, Israel

来源：

2009 IEEE INTERNATIONAL CONFERENCE ON ACOUSTICS, SPEECH, AND SIGNAL PROCESSING, VOLS 1- 8, PROCEEDINGS | 2009年

基金：

以色列科学基金会;

关键词：

iterative shrinkage-thresholding algorithm; least squares and l(1) regularization problems; optimal gradient method; two steps iterative algorithms; image deblurring; RESTORATION;

D O I：

10.1109/ICASSP.2009.4959678

中图分类号：

O42 [声学];

学科分类号：

070206 ; 082403 ;

摘要：

We consider the class of Iterative Shrinkage-Thresholding Algorithms (ISTA) for solving linear inverse problems arising in signal/image processing. This class of methods is attractive due to its simplicity, however, they are also known to converge quite slowly. In this paper we present a Fast Iterative Shrinkage-Thresholding Algorithm (FISTA) which preserves the computational simplicity of ISTA, but with a global rate of convergence which is proven to be significantly better, both theoretically and practically. Initial promising numerical results for wavelet-based image deblurring demonstrate the capabilities of FISTA.

引用

页码：693 / +

页数：2

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