UM
Spectral-spatial destriping of hyperspectral image via correntropy based sparse representation and unidirectional Huber-Markov random fields
Wang, Yulong1; Tang, Yuan Yan2; Li, Luoqing3
2017-11-19
Source PublicationINTERNATIONAL JOURNAL OF WAVELETS MULTIRESOLUTION AND INFORMATION PROCESSING
ISSN0219-6913
Volume15Issue:6
Abstract

This paper presents a novel destriping method for hyperspectral images. Most of the previous destriping methods regard only the corrupted subimage as an isolated image and fail to consider the high spectral correlation between the subimages in different bands. This may impede their performance of removing striping noises. The proposed method takes advantage of both spectral and spatial information to contribute to the process of striping noise reduction. Firstly, a correntropy-based sparse representation (CSR) model is utilized to learn the high spectral correlation between the subimages in different bands. Then the spatial information of the target subimage with striping noise is incorporated into the CSR model with a unidirectional Huber-Markov random field prior. We devise an Augmented Lagrange Multiplier type of algorithm to efficiently compute the destriped results. The experimental results on two real-world hyperspectral data sets demonstrate the effectiveness of the proposed method.

KeywordHyperspectral Images Destriping Sparse Representation Markov Random Field
DOIhttps://doi.org/10.1142/S0219691317500576
URLView the original
Indexed BySCI
Language英语
WOS Research AreaComputer Science ; Mathematics
WOS SubjectComputer Science, Software Engineering ; Mathematics, Interdisciplinary Applications
WOS IDWOS:000416435400004
PublisherWORLD SCIENTIFIC PUBL CO PTE LTD
The Source to ArticleWOS
Fulltext Access
Citation statistics
Cited Times [WOS]:1   [WOS Record]     [Related Records in WOS]
Document TypeJournal article
CollectionUniversity of Macau
Corresponding AuthorWang, Yulong; Tang, Yuan Yan; Li, Luoqing
Affiliation1.School of Information Science and Engineering, Chengdu University, Chengdu, 610106, P. R. China
2.Faculty of Science and Technology, University of Macau, Macau, 999078, P. R. China
3.Faculty of Mathematics and Statistics, Hubei University, Wuhan, 430062, P. R. China
Corresponding Author AffilicationFaculty of Science and Technology
Recommended Citation
GB/T 7714
Wang, Yulong,Tang, Yuan Yan,Li, Luoqing. Spectral-spatial destriping of hyperspectral image via correntropy based sparse representation and unidirectional Huber-Markov random fields[J]. INTERNATIONAL JOURNAL OF WAVELETS MULTIRESOLUTION AND INFORMATION PROCESSING,2017,15(6).
APA Wang, Yulong,Tang, Yuan Yan,&Li, Luoqing.(2017).Spectral-spatial destriping of hyperspectral image via correntropy based sparse representation and unidirectional Huber-Markov random fields.INTERNATIONAL JOURNAL OF WAVELETS MULTIRESOLUTION AND INFORMATION PROCESSING,15(6).
MLA Wang, Yulong,et al."Spectral-spatial destriping of hyperspectral image via correntropy based sparse representation and unidirectional Huber-Markov random fields".INTERNATIONAL JOURNAL OF WAVELETS MULTIRESOLUTION AND INFORMATION PROCESSING 15.6(2017).
Files in This Item:
There are no files associated with this item.
Related Services
Recommend this item
Bookmark
Usage statistics
Export to Endnote
Google Scholar
Similar articles in Google Scholar
[Wang, Yulong]'s Articles
[Tang, Yuan Yan]'s Articles
[Li, Luoqing]'s Articles
Baidu academic
Similar articles in Baidu academic
[Wang, Yulong]'s Articles
[Tang, Yuan Yan]'s Articles
[Li, Luoqing]'s Articles
Bing Scholar
Similar articles in Bing Scholar
[Wang, Yulong]'s Articles
[Tang, Yuan Yan]'s Articles
[Li, Luoqing]'s Articles
Terms of Use
No data!
Social Bookmark/Share
All comments (0)
No comment.
 

Items in the repository are protected by copyright, with all rights reserved, unless otherwise indicated.