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Compressed sensing of hyperspectral images based on scrambled block Hadamard ensemble

[+] Author Affiliations
Li Wang, Yan Feng

Northwestern Polytechnical University, School of Electronics and Information, 127 West Youyi Road, Xi’an 710072, China

J. Electron. Imaging. 25(6), 063021 (Dec 17, 2016). doi:10.1117/1.JEI.25.6.063021
History: Received July 17, 2016; Accepted November 21, 2016
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Abstract.  A fast measurement matrix based on scrambled block Hadamard ensemble for compressed sensing (CS) of hyperspectral images (HSI) is investigated. The proposed measurement matrix offers several attractive features. First, the proposed measurement matrix possesses Gaussian behavior, which illustrates that the matrix is universal and requires a near-optimal number of samples for exact reconstruction. In addition, it could be easily implemented in the optical domain due to its integer-valued elements. More importantly, the measurement matrix only needs small memory for storage in the sampling process. Experimental results on HSIs reveal that the reconstruction performance of the proposed measurement matrix is comparable or better than Gaussian matrix and Bernoulli matrix using different reconstruction algorithms while consuming less computational time. The proposed matrix could be used in CS of HSI, which would save the storage memory on board, improve the sampling efficiency, and ameliorate the reconstruction quality.

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Citation

Li Wang and Yan Feng
"Compressed sensing of hyperspectral images based on scrambled block Hadamard ensemble", J. Electron. Imaging. 25(6), 063021 (Dec 17, 2016). ; http://dx.doi.org/10.1117/1.JEI.25.6.063021


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