Image compressed sensing based on wavelet transform in contourlet domain

被引：20
|
作者：
Bi, Xue [1 ,2 ]
Chen, Xiang-dong [1 ]
Zhang, Yu [3 ]
Liu, Bin [1 ]
机构：
[1] SW Jiaotong Univ, Sch Informat Sci & Technol, Chengdu 610031, Peoples R China
[2] Xi Hua Univ, Network Ctr, Chengdu 610039, Peoples R China
[3] CNPC Chuanqing Drilling Engn Co Ltd, Drilling & Prod Technol Res Inst, Guanghan 618300, Peoples R China
来源：
SIGNAL PROCESSING | 2011年 / 91卷 / 05期
基金：
中国国家自然科学基金;
关键词：
Compressed sensing; Image reconstruction; Contourlet domain; Wavelet transform; DECOMPOSITION;
D O I：
10.1016/j.sigpro.2010.10.006
中图分类号：
TM [电工技术]; TN [电子技术、通信技术];
学科分类号：
0808 ; 0809 ;
摘要：
Compressed sensing (CS) has been widely concerned and sparsity of a signal plays a crucial role in CS to exactly recover signals. Contourlet transform provides sparse representations for images, so an algorithm of CS reconstruction based on contourlet is considered. Meanwhile, taking into account the computation and the storage of large random measurement matrices in the CS framework, we are trying to introduce the wavelet transform into the contourlet domain to reduce the size of random measurement matrices. Several numerical experiments demonstrate that this idea is feasible. The proposed algorithm possesses the following advantages: reduced size of random measurement matrix and improved recovered performance. (C) 2010 Elsevier B.V. All rights reserved.
引用
收藏
页码：1085 / 1092
页数：8
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