Projection-Based NMF for Hyperspectral Unmixing

doi:10.1109/JSTARS.2015.2427656

OPT OpenIR > 光谱成像技术研究室

	Projection-Based NMF for Hyperspectral Unmixing
	Yuan, Yuan; Feng, Yachuang; Lu, Xiaoqiang
	2015-06-01
发表期刊	IEEE JOURNAL OF SELECTED TOPICS IN APPLIED EARTH OBSERVATIONS AND REMOTE SENSING
卷号	8 期号:6 页码:2632-2643
摘要	As a widely concerned research topic, many advanced algorithms have been proposed for hyperspectral unmixing. However, they may fail to accurately identify endmember signatures when coming across insufficient spatial resolution. To deal with this problem, an algorithm based on semisupervised linear sparse regression is proposed, in which unmixing procedure is reduced to seeking an optimal subset from the spectral library to best model mixed pixels in the scene. However, the number of the spectra with nonzero abundance is much more than that of the true endmember signatures. Furthermore, the selection of library spectra as endmember signatures is undesirable due to the divergent imaging conditions. In this paper, a novel projection-based nonnegative matrix factorization (NMF) (PNMF) algorithm is proposed by importing spectra library into the NMF framework. The main novelties of this paper are listed as follows. 1) By introducing the spectral library, the extraction of endmember signatures is no longer restricted by spatial resolution. 2) Related spectra are selected and projected onto a subspace containing the endmember signatures. So that the number of endmember signatures is controlled by dimension of the subspace. 3) In PNMF, the endmember signatures are adaptively generated from the spectral library, and are matched with the observed hyperspectral images. This overcomes the difficulty caused by diverse imaging conditions, and makes the proposed algorithm more practical for real applications. The experimental results, conducted on both synthetic and real hyperspectral data, illustrate the advantages of the proposed algorithm when compared with the state-of-the-art algorithms.
文章类型	Article
关键词	Hyperspectral Unmixing Nonnegative Matrix Factorization (Nmf) Spectral Library Subspace Projection
WOS标题词	Science & Technology ; Technology ; Physical Sciences
DOI	10.1109/JSTARS.2015.2427656
收录类别	SCI ; EI
关键词[WOS]	NONNEGATIVE MATRIX FACTORIZATION ; SPECTRAL MIXTURE ANALYSIS ; VOLUME SIMPLEX ANALYSIS ; MATERIAL QUANTIFICATION ; ENDMEMBER EXTRACTION ; COMPONENT ANALYSIS ; FAST ALGORITHM ; IMAGERY ; REGULARIZATION ; SPARSITY
语种	英语
WOS研究方向	Engineering ; Physical Geography ; Remote Sensing ; Imaging Science & Photographic Technology
WOS类目	Engineering, Electrical & Electronic ; Geography, Physical ; Remote Sensing ; Imaging Science & Photographic Technology
WOS记录号	WOS:000359264000028
引用统计	被引频次：38[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/181661/25288
专题	光谱成像技术研究室
作者单位	Chinese Acad Sci, Xian Inst Opt & Precis Mech, State Key Lab Transient Opt & Photon, Ctr Opt Imagery Anal & Learning OPTIMAL, Xian 710119, Peoples R China
推荐引用方式 GB/T 7714	Yuan, Yuan,Feng, Yachuang,Lu, Xiaoqiang. Projection-Based NMF for Hyperspectral Unmixing[J]. IEEE JOURNAL OF SELECTED TOPICS IN APPLIED EARTH OBSERVATIONS AND REMOTE SENSING,2015,8(6):2632-2643.
APA	Yuan, Yuan,Feng, Yachuang,&Lu, Xiaoqiang.(2015).Projection-Based NMF for Hyperspectral Unmixing.IEEE JOURNAL OF SELECTED TOPICS IN APPLIED EARTH OBSERVATIONS AND REMOTE SENSING,8(6),2632-2643.
MLA	Yuan, Yuan,et al."Projection-Based NMF for Hyperspectral Unmixing".IEEE JOURNAL OF SELECTED TOPICS IN APPLIED EARTH OBSERVATIONS AND REMOTE SENSING 8.6(2015):2632-2643.

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