UM
Manifold-Based Sparse Representation for Hyperspectral Image Classification
Yuan Yan Tang1,2; Haoliang Yuan1; Luoqing Li3
2014-12
Source PublicationIEEE Transactions on Geoscience and Remote Sensing
ISSN1962892
Volume52Issue:12Pages:7606 - 7618
Abstract

A sparsity-based model has led to interesting results in hyperspectral image (HSI) classification. Sparse representation from a test sample is used to identify the class label. However, an l1-based sparse algorithm sometimes yields unstable sparse representation. Inspired by recent progress in manifold learning, two manifold-based sparse representation algorithms are proposed to exploit the local structure of the test samples in corresponding sparse representations for enforcing smoothness across neighboring samples' sparse representations. Using techniques from regularization and local invariance, two manifold-based regularization terms are incorporated into the l1-based objective function. Extensive experiments show that our proposed algorithms obtain excellent classification performance on three classic HSIs. 

KeywordClassification Hyperspectral Image (Hsi) Laplacian Eigenmap (Le) Locally Linear Embedding (Lle) Manifold Learning Sparse Representation
DOIhttps://doi.org/10.1109/TGRS.2014.2315209
URLView the original
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
PublisherIEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC, 445 HOES LANE, PISCATAWAY, NJ 08855-4141 USA
The Source to ArticleScopus
Fulltext Access
Citation statistics
Document TypeJournal article
CollectionUniversity of Macau
Corresponding AuthorYuan Yan Tang; Haoliang Yuan; Luoqing Li
Affiliation1.Faculty of Science and Technology, University of Macau, Macau 999078, China
2.College of Computer Science, Chongqing University, Chongqing 400000, China
3.Faculty of Mathematics and Statistics, Hubei University, Wuhan 430062, China
First Author AffilicationFaculty of Science and Technology
Corresponding Author AffilicationFaculty of Science and Technology
Recommended Citation
GB/T 7714
Yuan Yan Tang,Haoliang Yuan,Luoqing Li. Manifold-Based Sparse Representation for Hyperspectral Image Classification[J]. IEEE Transactions on Geoscience and Remote Sensing,2014,52(12):7606 - 7618.
APA Yuan Yan Tang,Haoliang Yuan,&Luoqing Li.(2014).Manifold-Based Sparse Representation for Hyperspectral Image Classification.IEEE Transactions on Geoscience and Remote Sensing,52(12),7606 - 7618.
MLA Yuan Yan Tang,et al."Manifold-Based Sparse Representation for Hyperspectral Image Classification".IEEE Transactions on Geoscience and Remote Sensing 52.12(2014):7606 - 7618.
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