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J4  2011, Vol. 45 Issue (4): 607-613    DOI: 10.3785/j.issn.1008-973X.2011.04.004
厉小润1, 伍小明1, 赵辽英2
1.浙江大学 电气工程学院,浙江 杭州 310027; 2.杭州电子科技大学 计算机应用技术研究所,浙江 杭州 310018
Unsupervised nonlinear decomposing method of
hyperspectral imagery
LI Xiao-run1, WU Xiao-ming1, ZHAO Liao-ying2
1. College of Electrical Engineering,Zhejiang University,Hangzhou 310027, China; 2. Institute of Computer
Application Technology, Hangzhou Dianzi University, Hangzhou 310018, China
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An unsupervised nonlinear decomposing algorithm for hyperspectral imagery was introduced to solve the nonlinear decomposing problem of hyperspectral imagery. The original data were mapped into a high-dimensional feature space by a nonlinear mapping, which was associated with a kernel function. Then the higher order relationships between the data were exploited. The mapped data became linearly separable in the high-dimensional feature space by using an appropriate nonlinear mapping. Then a linear nonnegative matrix factorization (NMF) method can be applied to extract more useful features. Endmember correlation coefficient, spectral angle distance, spectral information divergence and root mean square error were used to estimate the quality of the results. The experimental results of synthetic mixtures and a real image scene demonstrated that the method outperformed the nonnegative matrix factorization approach.

出版日期: 2011-05-05
:  TP 751  


作者简介: 厉小润(1970—),男,浙江东阳人,副教授,从事模式识别和遥感图像分析的研究.E-mail:
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厉小润, 伍小明, 赵辽英. 非监督的高光谱混合像元非线性分解方法[J]. J4, 2011, 45(4): 607-613.

LI Xiao-run, WU Xiao-ming, ZHAO Liao-ying. Unsupervised nonlinear decomposing method of
hyperspectral imagery. J4, 2011, 45(4): 607-613.


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