Double Constrained NMF for Hyperspectral Unmixing

doi:10.1109/TGRS.2013.2265322

OPT OpenIR > 光谱成像技术研究室

	Double Constrained NMF for Hyperspectral Unmixing
	Lu, Xiaoqiang1 ; Wu, Hao 2; Yuan, Yuan1
作者部门	光学影像学习与分析中心
	2014-05-01
发表期刊	IEEE TRANSACTIONS ON GEOSCIENCE AND REMOTE SENSING
ISSN	0196-2892
卷号	52 期号:5 页码:2746-2758
摘要	Given only the collected hyperspectral data, unmixing aims at obtaining the latent constituent materials and their corresponding fractional abundances. Recently, many nonnegative matrix factorization (NMF)-based algorithms have been developed to deal with this issue. Considering that the abundances of most materials may be sparse, the sparseness constraint is intuitively introduced into NMF. Although sparse NMF algorithms have achieved advanced performance in unmixing, the result is still susceptible to unstable decomposition and noise corruption. To reduce the aforementioned drawbacks, the structural information of the data is exploited to guide the unmixing. Since similar pixel spectra often imply similar substance constructions, clustering can explicitly characterize this similarity. Through maintaining the structural information during the unmixing, the resulting fractional abundances by the proposed algorithm can well coincide with the real distributions of constituent materials. Moreover, the additional clustering-based regularization term also lessens the interference of noise to some extent. The experimental results on synthetic and real hyperspectral data both illustrate the superiority of the proposed method compared with other state-of-the-art algorithms.
文章类型	Article
关键词	Clustering-based Regularization Hyperspectral Unmixing Mixed Pixel Nonnegative Matrix Factorization (Nmf)
WOS标题词	Science & Technology ; Physical Sciences ; Technology
DOI	10.1109/TGRS.2013.2265322
收录类别	SCI ; EI
关键词[WOS]	NONNEGATIVE MATRIX FACTORIZATION ; ENDMEMBER EXTRACTION ; COMPONENT ANALYSIS ; ALGORITHM ; IMAGERY
语种	英语
WOS研究方向	Geochemistry & Geophysics ; Engineering ; Remote Sensing ; Imaging Science & Photographic Technology
WOS类目	Geochemistry & Geophysics ; Engineering, Electrical & Electronic ; Remote Sensing ; Imaging Science & Photographic Technology
WOS记录号	WOS:000332484700038
引用统计	被引频次：111[WOS] [WOS记录] [WOS相关记录]
文献类型	期刊论文
条目标识符	http://ir.opt.ac.cn/handle/181661/22374
专题	光谱成像技术研究室
作者单位	1.Chinese Acad Sci, Xian Inst Opt & Precis Mech, State Key Lab Transient Opt & Photon, Ctr Opt Imagery Anal & Learning, Xian 710119, Peoples R China 2.Hubei Univ, Fac Math & Comp Sci, Wuhan 430062, Peoples R China
推荐引用方式 GB/T 7714	Lu, Xiaoqiang,Wu, Hao,Yuan, Yuan. Double Constrained NMF for Hyperspectral Unmixing[J]. IEEE TRANSACTIONS ON GEOSCIENCE AND REMOTE SENSING,2014,52(5):2746-2758.
APA	Lu, Xiaoqiang,Wu, Hao,&Yuan, Yuan.(2014).Double Constrained NMF for Hyperspectral Unmixing.IEEE TRANSACTIONS ON GEOSCIENCE AND REMOTE SENSING,52(5),2746-2758.
MLA	Lu, Xiaoqiang,et al."Double Constrained NMF for Hyperspectral Unmixing".IEEE TRANSACTIONS ON GEOSCIENCE AND REMOTE SENSING 52.5(2014):2746-2758.

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