CASIA OpenIR  > 模式识别国家重点实验室  > 先进数据分析与学习
Multicluster Spatial-Spectral Unsupervised Feature Selection for Hyperspectral Image Classification
Li, Haichang; Xiang, Shiming; Zhong, Zisha; Ding, Kun; Pan, Chunhong; haichang516@gmail.com
Source PublicationIEEE GEOSCIENCE AND REMOTE SENSING LETTERS
2015-08-01
Volume12Issue:8Pages:1660-1664
SubtypeArticle
AbstractA new unsupervised spatial-spectral feature selection method for hyperspectral images has been proposed in this letter. The key idea is to select the features that better preserve the multicluster structure of the multiple spatial-spectral features. Specifically, the multicluster structure information is obtained through spectral clustering utilizing a weighted combination of the multiple features. Then, such information is preserved in a group-sparsity- based robust linear regression model. The features that contribute more in preserving the multicluster structure information are selected. Comparative experiments on two popular real hyperspectral images validate the effectiveness of the proposed method, showing higher classification accuracy.
KeywordClustering Feature Selection Hyperspectral Spatial-spectral
WOS HeadingsScience & Technology ; Physical Sciences ; Technology
WOS KeywordBAND SELECTION ; REGRESSION
Indexed BySCI
Language英语
WOS Research AreaGeochemistry & Geophysics ; Engineering ; Remote Sensing ; Imaging Science & Photographic Technology
WOS SubjectGeochemistry & Geophysics ; Engineering, Electrical & Electronic ; Remote Sensing ; Imaging Science & Photographic Technology
WOS IDWOS:000356542100014
Citation statistics
Document Type期刊论文
Identifierhttp://ir.ia.ac.cn/handle/173211/7916
Collection模式识别国家重点实验室_先进数据分析与学习
Corresponding Authorhaichang516@gmail.com
AffiliationChinese Acad Sci, Inst Automat, Beijing 100190, Peoples R China
Recommended Citation
GB/T 7714
Li, Haichang,Xiang, Shiming,Zhong, Zisha,et al. Multicluster Spatial-Spectral Unsupervised Feature Selection for Hyperspectral Image Classification[J]. IEEE GEOSCIENCE AND REMOTE SENSING LETTERS,2015,12(8):1660-1664.
APA Li, Haichang,Xiang, Shiming,Zhong, Zisha,Ding, Kun,Pan, Chunhong,&haichang516@gmail.com.(2015).Multicluster Spatial-Spectral Unsupervised Feature Selection for Hyperspectral Image Classification.IEEE GEOSCIENCE AND REMOTE SENSING LETTERS,12(8),1660-1664.
MLA Li, Haichang,et al."Multicluster Spatial-Spectral Unsupervised Feature Selection for Hyperspectral Image Classification".IEEE GEOSCIENCE AND REMOTE SENSING LETTERS 12.8(2015):1660-1664.
Files in This Item: Download All
File Name/Size DocType Version Access License
Multicluster Spatial(526KB)期刊论文出版稿开放获取CC BY-NC-SAView Download
Related Services
Recommend this item
Bookmark
Usage statistics
Export to Endnote
Google Scholar
Similar articles in Google Scholar
[Li, Haichang]'s Articles
[Xiang, Shiming]'s Articles
[Zhong, Zisha]'s Articles
Baidu academic
Similar articles in Baidu academic
[Li, Haichang]'s Articles
[Xiang, Shiming]'s Articles
[Zhong, Zisha]'s Articles
Bing Scholar
Similar articles in Bing Scholar
[Li, Haichang]'s Articles
[Xiang, Shiming]'s Articles
[Zhong, Zisha]'s Articles
Terms of Use
No data!
Social Bookmark/Share
File name: Multicluster Spatial–Spectral Unsupervised Feature Selection for Hyperspectral Image Classificatio_GRSL_2015.pdf
Format: Adobe PDF
All comments (0)
No comment.
 

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