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New recovery algorithm for compressed sensing based on structured sparse model.
Pages: 203-206
Year: Issue:  14
Journal: Computer Engineering and Applications

Keyword:  Compressed Sensing(CS)structured sparse modeldual-tree complex wavelet transform;
Abstract: Recently, normal recovery algorithms for CS only use signal and image sparse priors under wavelet, make no use of the tree structure priors. In order to reconstruct the original signal quickly and accurately, this paper brings the tree structure sparse model into SP algorithm , CoSaMP-algorithm and gets the improved recovery algorithm for compressed sensing. Combin-ing with structured sparse model and dual-tree complex wavelet transform, a new recovery algorithm for CS is proposed. The simulated results show that the algorithm can achieve higher reconstructed image performance.
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