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中文摘要：
压缩感知（Compressive Sensing,CS）理论是在已知信号具有稀疏性或可压缩性的条件下,对信号数据进行采集、编解码的新理论.将压缩感知应用于图像压缩具有潜在的应用价值,压缩感知图像重建算法是该领域的热点问题.在对目前压缩感知重建算法的文献进行分析和综合的基础上,首先阐述了压缩感知的基本原理及其各项关键技术,然后简要总结了当前流行的压缩感知图像重建算法,给出了各种图像重建算法的仿真结果及分析,最后对影响压缩感知图像重建算法几个关键问题进行剖析和展望.
英文摘要：
Compressive Sensing（CS） theory is a novel data collection and coding theory under the condition that signal is sparse or compressible.Image compression base on CS has potential application value,and the CS based image reconstruction algorithm is a hot topic.In the basis of many related literatures,an overview on the state of the art of image reconstruction algorithms is given in this paper.Firstly,the CS foundations and its several key problems are introduced.Then,the current popular CS based image reconstruction algorithms are presented,and the experiment results and analysis of these algorithms are described.At the end,the key problems in CS based image reconstruction algorithm are summarized and prospected.
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