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Hyperspectral image band selection via global optimal clustering
Zhang, Fahong1; Wang, Qi1; Li, Xuelong2
2017-12-01
会议名称37th Annual IEEE International Geoscience and Remote Sensing Symposium, IGARSS 2017
会议录名称2017 IEEE International Geoscience and Remote Sensing Symposium: International Cooperation for Global Awareness, IGARSS 2017 - Proceedings
卷号2017-July
页码1-4
会议日期2017-07-23
会议地点Fort Worth, TX, United states
出版者Institute of Electrical and Electronics Engineers Inc.
产权排序2
摘要

Band selection, by choosing a set of representative bands in hyperspectral images (HSI), is concerned to be an effective method to eliminate the 'Hughes phenomenon'. In this paper, we present a global optimal clustering-based band selection (GOC) algorithm based on the hypothesis that all the bands in a cluster are continuous at their wavelengths. After the clustering result is obtained, we propose a greedy-based method to select representative bands in each cluster, trying to minimize the linear reconstruction error. Experiment on a real HSI dataset shows that the proposed method outperforms the state-of-the-art competitors. © 2017 IEEE.

作者部门光学影像学习与分析中心
DOI10.1109/IGARSS.2017.8126818
收录类别EI ; ISTP
ISBN号9781509049516
语种英语
引用统计
文献类型会议论文
条目标识符http://ir.opt.ac.cn/handle/181661/29941
专题光学影像学习与分析中心
通讯作者Wang, Qi
作者单位1.School of Computer Science, Center for OPTical IMagery Analysis and Learning, Northwestern Polytechnical University, Xi'an, Shaanxi, 710072, China
2.Center for OPTical IMagery Analysis and Learning, Xi'An Institute of Optics and Precision Mechanics, Chinese Academy of Sciences, Xi'an, Shaanxi, 710119, China
推荐引用方式
GB/T 7714
Zhang, Fahong,Wang, Qi,Li, Xuelong. Hyperspectral image band selection via global optimal clustering[C]:Institute of Electrical and Electronics Engineers Inc.,2017:1-4.
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