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题名:
Hyperspectral target detection based on improved automatic morphological endmember extraction method
作者: Sun, Xu-Guang1,2; Cai, Jing-Ju2; Xu, Zhi-Yong2; Zhang, Jian-Lin2
出版日期: 2012
会议名称: Proceedings of SPIE: 6th International Symposium on Advanced Optical Manufacturing and Testing Technologies: Large Mirrors and Telescopes
会议日期: 2012
DOI: 10.1117/12.976015
通讯作者: Sun, X.-G.
中文摘要: At present, commonly endmember extraction of hyperspectral is mainly concentrated in the spectral region. Because the spatial information is not used enough, the endmember extraction is not precise which can lead to a bad result of mixed pixel decomposition and hyperspectral target detection. Actually, the distribution of endmembers in space has a certain shape and aggregation .By making use of these information we can extract more precise endmembers. Automatic morphological endmember extraction technology can make full use of abundant spectral information and spatial information. This paper based on the existed automatic morphological algorithm, presents a method in combination with maximum distance for morphological endmember extraction to solve the influence of spectral variations, which effectively extracts different classes of endmember curves. Based on the theory of orthogonal subspace projection, the authors propose an improved constrained energy minimization (CEM) algorithm, achieve better hyperspectral target detection results. © 2012 SPIE.
英文摘要: At present, commonly endmember extraction of hyperspectral is mainly concentrated in the spectral region. Because the spatial information is not used enough, the endmember extraction is not precise which can lead to a bad result of mixed pixel decomposition and hyperspectral target detection. Actually, the distribution of endmembers in space has a certain shape and aggregation .By making use of these information we can extract more precise endmembers. Automatic morphological endmember extraction technology can make full use of abundant spectral information and spatial information. This paper based on the existed automatic morphological algorithm, presents a method in combination with maximum distance for morphological endmember extraction to solve the influence of spectral variations, which effectively extracts different classes of endmember curves. Based on the theory of orthogonal subspace projection, the authors propose an improved constrained energy minimization (CEM) algorithm, achieve better hyperspectral target detection results. © 2012 SPIE.
收录类别: Ei
语种: 英语
卷号: 8415
ISSN号: 0277786X
文章类型: 会议论文
页码: 841518
Citation statistics:
内容类型: 会议论文
URI标识: http://ir.ioe.ac.cn/handle/181551/7690
Appears in Collections:光电探测与信号处理研究室(五室)_会议论文

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作者单位: 1. Graduate University, Chinese Academy of Science, Beijing, 100190, China
2. Institute of Optics and Electronics, Chinese Academy of Sciences, Chengdu, 610209, China

Recommended Citation:
Sun, Xu-Guang,Cai, Jing-Ju,Xu, Zhi-Yong,et al. Hyperspectral target detection based on improved automatic morphological endmember extraction method[C]. 见:Proceedings of SPIE: 6th International Symposium on Advanced Optical Manufacturing and Testing Technologies: Large Mirrors and Telescopes. 2012.
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