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Optimal neighboring reconstruction for hyperspectral band selection
Zhang, Fahong1; Wang, Qi1,2; Li, Xuelong3,4
2018-10-31
Conference Name38th Annual IEEE International Geoscience and Remote Sensing Symposium, IGARSS 2018
Source Publication2018 IEEE International Geoscience and Remote Sensing Symposium, IGARSS 2018 - Proceedings
Volume2018-July
Pages4709-4712
Conference Date2018-07-22
Conference PlaceValencia, Spain
PublisherInstitute of Electrical and Electronics Engineers Inc.
Contribution Rank3
AbstractBand selection, as an effective and popular dimensional reduction methods for hyperspectral image (HSI), has raised wide attention in recent years. In this paper, we propose a novel band selection method called optimal neighboring reconstruction (ONR). Compared to conventional methods, ONR mainly has following advantages. 1) It is globally optimal, which means the best combination of bands towards the designed objective function can be achieved. 2) It sufficiently exploits the neighboring structure among bands, so can effectively reduce the redundancy while maintaining the discrimination among bands. Experiments on three real data sets show that the proposed method has excellent performance. © 2018 IEEE
Department光学影像学习与分析中心
DOI10.1109/IGARSS.2018.8517884
Indexed ByEI
ISBN9781538671504
Language英语
EI Accession Number20191206669487
Citation statistics
Document Type会议论文
Identifierhttp://ir.opt.ac.cn/handle/181661/31390
Collection光学影像学习与分析中心
Affiliation1.School of Computer Science, Center for OPTical IMagery Analysis and Learning, Northwestern Polytechnical University, Xi'an, Shaanxi; 710072, China;
2.Unmanned System Research Institute, Northwestern Polytechnical University, Xi'an, Shaanxi; 710072, China;
3.Xi'an Institute of Optics and Precision Mechanics, Chinese Academy of Sciences, Xi'an, Shaanxi; 710119, China;
4.University of Chinese, Academy of Sciences, Beijing; 100049, China
Recommended Citation
GB/T 7714
Zhang, Fahong,Wang, Qi,Li, Xuelong. Optimal neighboring reconstruction for hyperspectral band selection[C]:Institute of Electrical and Electronics Engineers Inc.,2018:4709-4712.
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