Image compressed sensing based on wavelet transform in contourlet domain

Authors:
Xue Bi;Xiang-Dong Chen;Yu Zhang;Bin Liu
Affiliations:
School of Information Science and Technology, Southwest Jiaotong University, Chengdu 610031, China and Network Center, Xi Hua University, Chengdu 610039, China;School of Information Science and Technology, Southwest Jiaotong University, Chengdu 610031, China;Drilling and Production Technology Research Institute, CNPC Chuanqing Drilling Engineering Company Limited, Guanghan 618300, China;School of Information Science and Technology, Southwest Jiaotong University, Chengdu 610031, China
Venue:
Signal Processing
Year:
2011

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Abstract

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.