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Optimal Clustering Framework for Hyperspectral Band Selection
Wang, Qi1,2,3; Zhang, Fahong1,2; Li, Xuelong4,5
Department光学影像学习与分析中心
2018-10
Source PublicationIEEE TRANSACTIONS ON GEOSCIENCE AND REMOTE SENSING
ISSN0196-2892
Volume56Issue:10Pages:5910-5922
Contribution Rank4
Abstract

Band selection, by choosing a set of representative bands in a hyperspectral image, is an effective method to reduce the redundant information without compromising the original contents. Recently, various unsupervised band selection methods have been proposed, but most of them are based on approximation algorithms which can only obtain suboptimal solutions toward a specific objective function. This paper focuses on clustering-based band selection and proposes a new framework to solve the above dilemma, claiming the following contributions: 1) an optimal clustering framework, which can obtain the optimal clustering result for a particular form of objective function under a reasonable constraint; 2) a rank on clusters strategy, which provides an effective criterion to select bands on existing clustering structure; and 3) an automatic method to determine the number of the required bands, which can better evaluate the distinctive information produced by certain number of bands. In experiments, the proposed algorithm is compared with some state-of-the-art competitors. According to the experimental results, the proposed algorithm is robust and significantly outperforms the other methods on various data sets.

KeywordDynamic Programming (Dp) Hyperspectral Band Selection Normalized Cut (Nc) Spectral Clustering (Sc)
DOI10.1109/TGRS.2018.2828161
Indexed BySCI ; EI
Language英语
WOS IDWOS:000446300700027
PublisherIEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC
EI Accession Number20182005188374
Citation statistics
Document Type期刊论文
Identifierhttp://ir.opt.ac.cn/handle/181661/30668
Collection光学影像学习与分析中心
Corresponding AuthorWang, Qi
Affiliation1.Northwestern Polytech Univ, Sch Comp Sci, Xian 710072, Shaanxi, Peoples R China
2.Northwestern Polytech Univ, Ctr Opt Imagery Anal & Learning, Xian 710072, Shaanxi, Peoples R China
3.Northwestern Polytech Univ, Unmanned Syst Res Inst, Xian 710072, Shaanxi, Peoples R China
4.Chinese Acad Sci, Xian Inst Opt & Precis Mech, Xian 710119, Shaanxi, Peoples R China
5.Univ Chinese Acad Sci, Beijing 100049, Peoples R China
Recommended Citation
GB/T 7714
Wang, Qi,Zhang, Fahong,Li, Xuelong. Optimal Clustering Framework for Hyperspectral Band Selection[J]. IEEE TRANSACTIONS ON GEOSCIENCE AND REMOTE SENSING,2018,56(10):5910-5922.
APA Wang, Qi,Zhang, Fahong,&Li, Xuelong.(2018).Optimal Clustering Framework for Hyperspectral Band Selection.IEEE TRANSACTIONS ON GEOSCIENCE AND REMOTE SENSING,56(10),5910-5922.
MLA Wang, Qi,et al."Optimal Clustering Framework for Hyperspectral Band Selection".IEEE TRANSACTIONS ON GEOSCIENCE AND REMOTE SENSING 56.10(2018):5910-5922.
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