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Fast OMP reconstruction for compressive hyperspectral imaging using joint spatial-spectral sparsity model
Liu, Haiying1; Chen, Rongli2; Wang, Yajun2; Lv, Pei2
2018
Conference Name10th International Conference on Information Optics and Photonics
Source PublicationTenth International Conference on Information Optics and Photonics
Volume10964
Conference Date2018-07-08
Conference PlaceBeijing, China
PublisherSPIE
Contribution Rank2
AbstractHyperspectral imaging typically produces huge data volume that demands enormous computational resources in terms of storage, computation and transmission, particularly when real-time processing is desired. In this paper, we study a lowcomplexity scheme for hyperspectral imaging completely bypassing high-complexity compression task. In this scheme, compressive hyperspectral data are acquired directly by a device similar to the single-pixel camera based on the principle of compressive sensing (CS). To decode the compressive data, we propose a flexible recovery strategy by taking advantage of the joint spatial-spectral correlation model of hyperspectral images. Moreover, a thorough investigation is analytically conducted on compressive hyperspectral data and we find that the compressive data still have strong spectral correlation. To make the recovery more accurate, an adaptive spectral band reordering algorithm is directly added to the compressive data before the reconstruction by making best use of spectral correlation. The real hyperspectral images are tested to demonstrate the feasibility and efficiency of the proposed algorithm. Experimental results indicate that the proposed recover algorithm can speed up the reconstruction process with reliable recovery quality. © 2018 SPIE.
Department先进光学仪器研究室
DOI10.1117/12.2504270
Indexed ByEI
ISBN9781510625792
Language英语
ISSN0277786X;1996771X
EI Accession Number20190206347247
Citation statistics
Document Type会议论文
Identifierhttp://ir.opt.ac.cn/handle/181661/31129
Collection先进光学仪器研究室
Corresponding AuthorLv, Pei
Affiliation1.School of Information Engineering, Chang'an University, Xi'an; 710064, China;
2.Xi'an Institute of Optics and Precision Mechanics, Chinese Academy of Sciences, Xi'an; 710119, China
Recommended Citation
GB/T 7714
Liu, Haiying,Chen, Rongli,Wang, Yajun,et al. Fast OMP reconstruction for compressive hyperspectral imaging using joint spatial-spectral sparsity model[C]:SPIE,2018.
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