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Discriminant Analysis with graph learning for hyperspectral image classification
Chen, Mulin1; Wang, Qi1,2; Li, Xuelong3,4; Wang, Qi (crabwq@gmail.com)
Department光学影像学习与分析中心
2018-06-01
Source PublicationRemote Sensing
ISSN20724292
Volume10Issue:6
Contribution Rank3
Abstract

Linear Discriminant Analysis (LDA) is a widely-used technique for dimensionality reduction, and has been applied in many practical applications, such as hyperspectral image classification. Traditional LDA assumes that the data obeys the Gaussian distribution. However, in real-world situations, the high-dimensional data may be with various kinds of distributions, which restricts the performance of LDA. To reduce this problem, we propose the Discriminant Analysis with Graph Learning (DAGL) method in this paper. Without any assumption on the data distribution, the proposed method learns the local data relationship adaptively during the optimization. The main contributions of this research are threefold: (1) the local data manifold is captured by learning the data graph adaptively in the subspace; (2) the spatial information within the hyperspectral image is utilized with a regularization term; and (3) an efficient algorithm is designed to optimize the proposed problem with proved convergence. Experimental results on hyperspectral image datasets show that promising performance of the proposed method, and validates its superiority over the state-of-the-art. ? 2018 by the authors.

DOI10.3390/rs10060836
Indexed BySCI ; EI
Language英语
EI Keywords20182605375984
Citation statistics
Cited Times:8[WOS]   [WOS Record]     [Related Records in WOS]
Document Type期刊论文
Identifierhttp://ir.opt.ac.cn/handle/181661/30412
Collection光学影像学习与分析中心
Corresponding AuthorWang, Qi (crabwq@gmail.com)
Affiliation1.School of Computer Science and Center for OPTical IMagery Analysis and Learning (OPTIMAL), Northwestern Polytechnical University, Xi'an; 710072, China
2.Unmanned System Research Institute, Northwestern Polytechnical University, Xi'an; 710072, China
3.Xi'an Institute of Optics and Precision Mechanics, Chinese Academy of Sciences, Xi'an; 710119, China
4.University of Chinese Academy of Sciences, Beijing; 100049, China
Recommended Citation
GB/T 7714
Chen, Mulin,Wang, Qi,Li, Xuelong,et al. Discriminant Analysis with graph learning for hyperspectral image classification[J]. Remote Sensing,2018,10(6).
APA Chen, Mulin,Wang, Qi,Li, Xuelong,&Wang, Qi .(2018).Discriminant Analysis with graph learning for hyperspectral image classification.Remote Sensing,10(6).
MLA Chen, Mulin,et al."Discriminant Analysis with graph learning for hyperspectral image classification".Remote Sensing 10.6(2018).
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