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国家自然科学基金(SBK201022367)

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发文基金:国家教育部博士点基金国家自然科学基金更多>>
相关领域:理学自动化与计算机技术更多>>

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Compressed image sensing with components regularization based on Bregman iteration
2011年
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.
LI Xing-xiuWEI Zhi-huiXIAO Liang
关键词:CS
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