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题名: Normal Endmember Spectral Unmixing Method for Hyperspectral Imagery
作者: Zhuang, Lina1; Zhang, Bing1; Gao, Lianru1; Li, Jun1; Plaza, Antonio1
刊名: IEEE JOURNAL OF SELECTED TOPICS IN APPLIED EARTH OBSERVATIONS AND REMOTE SENSING
出版日期: 2015
卷号: 8, 期号:6(SI), 页码:16293-16314
关键词: Endmember variability ; hyperspectral imaging ; normal compositional model (NCM) ; normal endmember spectral unmixing (NESU) ; particle swarm optimization (PSO) ; spectral unmixing
DOI: 10.1109/JSTARS.2014.2360888
通讯作者: Gao, LR (reprint author), Chinese Acad Sci, Key Lab Digital Earth Sci, Inst Remote Sensing & Digital Earth, Beijing 100094, Peoples R China.
文章类型: Article
英文摘要: The normal compositional model (NCM) has been introduced to characterize mixed pixels in hyperspectral images, particularly when endmember variability needs to be considered in the unmixing process. Each pixel is modeled as a linear combination of endmembers, which are treated as Gaussian random variables in order to capture such spectral variability. Since the combination coefficients (i.e., abundances) and the endmembers are unknown variables at the same time in the NCM, the parameter estimation is more difficult in comparison with conventional approaches. In order to address this issue, we propose a new Bayesian method, termed normal endmember spectral unmixing (NESU), for improved parameter estimation in this context. It considers the endmembers as known variables (resulting from the extraction of endmember bundles), then performs optimal estimations of the remaining unknown parameters, i.e., the abundances, using Bayesian inference. The particle swarm optimization (PSO) technique is adopted to estimate the optimal values of abundances according to their posterior probabilities. The performance of the proposed algorithm is evaluated using both synthetic and real hyperspectral data. The obtained results demonstrate that the proposed method leads to significant improvements in terms of unmixing accuracies.
研究领域[WOS]: Engineering, Electrical & Electronic ; Geography, Physical ; Remote Sensing ; Imaging Science & Photographic Technology
收录类别: SCI ; EI
项目资助者: National Natural Science Foundation of China [41325004] ; Key Research Program of the Chinese Academy of Sciences [KZZD-EW-TZ-18] ; Foundation of Director of Institute of Remote Sensing and Digital Earth, Chinese Academy of Sciences, China [Y3ZZ27101B]
语种: 英语
WOS记录号: WOS:000359264000025
Citation statistics:
内容类型: 期刊论文
版本: 出版稿
URI标识: http://ir.radi.ac.cn/handle/183411/37504
Appears in Collections:SCI/EI期刊论文_期刊论文

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作者单位: 1.[Zhuang, Lina
2.Zhang, Bing
3.Gao, Lianru] Chinese Acad Sci, Key Lab Digital Earth Sci, Inst Remote Sensing & Digital Earth, Beijing 100094, Peoples R China
4.[Zhuang, Lina] Univ Chinese Acad Sci, Beijing 100049, Peoples R China
5.[Li, Jun] Sun Yat Sen Univ, Guangdong Key Lab Urbanizat & Geosimulat, Sch Geog & Planning, Guangzhou 510275, Guangdong, Peoples R China
6.[Plaza, Antonio] Univ Extremadura, Hyperspectral Comp Lab, Dept Technol Comp & Commun, Cacerres 10071, Spain

Recommended Citation:
Zhuang L(庄丽娜). Normal Endmember Spectral Unmixing Method for Hyperspectral Imagery[J]. IEEE JOURNAL OF SELECTED TOPICS IN APPLIED EARTH OBSERVATIONS AND REMOTE SENSING,2014(1).
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文件名: Zhuang-2015-Normal Endmember Spectral Unmixing.pdf
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