Compressed image sensing with components regularization based on Bregman iteration

doi:10.1016/S1005-8885(10)60053-2

中国邮电高校学报(英文) ›› 2011, Vol. 18 ›› Issue (2): 114-119.doi: 10.1016/S1005-8885(10)60053-2

Compressed image sensing with components regularization based on Bregman iteration

李星秀¹,韦志辉²

1. 南京理工大学
2.

收稿日期:2010-08-11 修回日期:2010-11-15 出版日期:2011-04-30 发布日期:2011-04-15
通讯作者: 李星秀 E-mail:xxlwpl@126.com
基金资助:
国家自然科学基金;高等教育博士点专项研究基金

Compressed image sensing with components regularization based on Bregman iteration

Received:2010-08-11 Revised:2010-11-15 Online:2011-04-30 Published:2011-04-15
Contact: Xing-Xiu LI E-mail:xxlwpl@126.com

摘要/Abstract

摘要：

Compressed sensing (CS) is a new theory of signal processing for simultaneous signal sampling and compression. The optimization methods with components regularization have been proposed to perform CS reconstruction of the natural images which always contain various morphological components. In this paper, in order to solve the components regularized optimization problem more accurately, an iterative algorithm is proposed based on the Bregman iteration. The proposed algorithm is an inner-outer iterative procedure, with the two-variable Bregman iteration as its outer iteration and the alternating minimization as its inner iteration. Experimental results show the superiority of the proposed algorithm to other recently developed algorithms in terms of the visual quality improvement and the detail feature preserving capability.

关键词:

CS, image reconstruction, Bregman iteration, components regularization

Abstract:

Key words:

CS, image reconstruction, Bregman iteration, components regularization

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Compressed image sensing with components regularization based on Bregman iteration

Compressed image sensing with components regularization based on Bregman iteration

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