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Spectral-spatial hyperspectral image destriping using low-rank representation and Huber-Markov random fields
Yulong Wang; Yuan Yan Tang; Lina Yang; Haoliang Yuan; Huiwu Luo; Yang Lu
2014
Conference Name2014 IEEE International Conference on Systems, Man, and Cybernetics (SMC)
Source PublicationConference Proceedings - IEEE International Conference on Systems, Man and Cybernetics
Volume2014-January
IssueJanuary
Pages305-310
Conference Date5-8 Oct. 2014
Conference PlaceSan Diego, CA
CountryUSA
PublisherIEEE, 345 E 47TH ST, NEW YORK, NY 10017 USA
Abstract

This paper presents a novel spectral-spatial destriping method for hyperspectral images. The ubiquitous striping noise in hyperspectral images might degrade the quality of the imagery and bring difficulties in hyperspectral data processing. Although numerous methods have been proposed for striping noise reduction recently, most of them fail to consider the spectral correlation and spatial information of the hyperspectral images simultaneously. In order to remedy this drawback, the proposed method integrates the spectral and spatial information to remove the striping noise in the hyperspectral images. To this end, firstly, the low-rank representation (LRR) is used to take advantage of the spectral information. Then, the spatial information is included using a Huber-Markov random field (MRF) prior model, which is convex and can well preserve the edge and texture information while removing the noise. The experimental results on simulated and real hyperspectral data sets demonstrate the effectiveness of the proposed method.

DOIhttps://doi.org/10.1109/SMC.2014.6973925
URLView the original
Language英语
WOS Research AreaComputer Science
WOS SubjectComputer Science, Artificial Intelligence ; Computer Science, Cybernetics ; Computer Science, Information Systems
WOS IDWOS:000370963700052
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Cited Times [WOS]:2   [WOS Record]     [Related Records in WOS]
Document TypeConference paper
CollectionDEPARTMENT OF COMPUTER AND INFORMATION SCIENCE
AffiliationDepartment of Computer and Information Science University of Macau Macau, China
First Author AffilicationUniversity of Macau
Recommended Citation
GB/T 7714
Yulong Wang,Yuan Yan Tang,Lina Yang,et al. Spectral-spatial hyperspectral image destriping using low-rank representation and Huber-Markov random fields[C]:IEEE, 345 E 47TH ST, NEW YORK, NY 10017 USA,2014:305-310.
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