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The Application of Wavelet-Based Contourlet Transform on Compressed Sensing
Du M(杜梅); Zhao HC(赵怀慈); Zhao CY(赵春阳); Li B(李波)
Department光电信息技术研究室
Conference Name2012 International Conference on Multimedia and Signal Processing
Conference DateDecember 7-9, 2012
Conference PlaceShanghai, China
Source Publication2012 International Conference on Multimedia and Signal Processing
2012
Pages570-577
Indexed ByEI ; CPCI(ISTP)
EI Accession number20133416655084
WOS IDWOS:000313664700072
Contribution Rank1
KeywordSparse Representation Wavelet-based Contourlet Transform Block Compressed Sensing Iterative Hard Thresholding Algorithm
AbstractReasonable sparse representation of signals are one of the key factors to ensure the quality of compressed sampling, so a proper sparse representing methods should be selected to make the signals sparse to the greatest extent in the applications of compressed sensing. In this paper we employed the wavelet-based contourlet transform, an improved contourlet transform, to decompose 2D images, adopted the framework of block compressed sensing to sample the images, and used the iterative hard thresholding algorithm to reconstruct the original images. Numerical experiments indicated that the runtime of the reconstruction algorithm adopting wavelet-based contourlet transform is the shortest compared to that adopting contourlet transform and that adopting wavelet transform; under low compression ratios, the quality of the reconstructed images using wavelet-based contourlet transform is superior to that using contourlet transform and that using traditional wavelet transform.
Language英语
Citation statistics
Document Type会议论文
Identifierhttp://ir.sia.cn/handle/173321/10176
Collection光电信息技术研究室
Affiliation1.Department of Optical-Electronics and Information Processing, Shenyang Institute of Automation, Chinese Academy of Science, Shenyang, 110016, China
2.Graduate School of Chinese Academy of Science, Beijing, 100049, China
3.Key Laboratory of Optical-Electronics Information Processing, Chinese Academy of Science, Shenyang, 110016, China
4.Key Laboratory of Image Understanding and Computer Vision, Liaoning Province, Shenyang, 110016, China
Recommended Citation
GB/T 7714
Du M,Zhao HC,Zhao CY,et al. The Application of Wavelet-Based Contourlet Transform on Compressed Sensing[C],2012:570-577.
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