The cosparse analysis model and algorithms

被引:303
作者
Nam, S. [1 ]
Davies, M. E. [2 ]
Elad, M. [3 ]
Gribonval, R. [1 ]
机构
[1] Ctr Rech INRIA Rennes Bretagne Atlantique, F-35042 Rennes, France
[2] Univ Edinburgh, Sch Engn & Elect, Edinburgh EH9 3JL, Midlothian, Scotland
[3] Technion Israel Inst Technol, Dept Comp Sci, IL-32000 Haifa, Israel
关键词
Synthesis; Analysis; Sparse representations; Union of subspaces; Pursuit algorithms; Greedy algorithms; Compressed-sensing; SPARSE REPRESENTATIONS; UNCERTAINTY PRINCIPLES; SIGNALS; DICTIONARIES; TRANSFORM; UNION;
D O I
10.1016/j.acha.2012.03.006
中图分类号
O29 [应用数学];
学科分类号
070104 ;
摘要
After a decade of extensive study of the sparse representation synthesis model, we can safely say that this is a mature and stable field, with clear theoretical foundations, and appealing applications. Alongside this approach, there is an analysis counterpart model, which, despite its similarity to the synthesis alternative, is markedly different. Surprisingly, the analysis model did not get a similar attention, and its understanding today is shallow and partial. In this paper we take a closer look at the analysis approach, better define it as a generative model for signals, and contrast it with the synthesis one. This work proposes effective pursuit methods that aim to solve inverse problems regularized with the analysis-model prior, accompanied by a preliminary theoretical study of their performance. We demonstrate the effectiveness of the analysis model in several experiments, and provide a detailed study of the model associated with the 2D finite difference analysis operator, a close cousin of the TV norm. (C) 2012 Elsevier Inc. All rights reserved.
引用
收藏
页码:30 / 56
页数:27
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