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中文摘要：
(CS ) 察觉到压缩是为同时的信号采样和压缩的信号处理的一个新理论。有部件规则化的优化方法被建议了执行总是包含各种各样的词法部件的自然图象的 CS 重建。在这份报纸，调整了以便解决部件优化问题更精确地，一个反复的算法基于 Bregman 重复被建议。建议算法是一个内部外部的反复的过程，与象它的外部重复的二变量的 Bregman 重复和象它的内部重复的轮流出现的最小化。试验性的结果以视觉优秀改进和保存能力的详细特征显示出建议算法的优势到另外的最近发达的算法。
英文摘要：
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.
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