[1] [1] Tong Qingxi, Zhang Bing, Zheng Lanfen. Hyperspectral Remote Sensing［M］. Beijing：Higher Education Press, 2006. 255～262

[2] [2] C. I. Chang, X. L. Zhao, M. L. G. Althouse et al.. Least squares subspace projection approach to mixed pixel classification for hyperspectral images［J］. IEEE Trans. Geoscience and Remote Sensing, 1998, 36(3): 898～912

[3] [3] H. Kwon, N. M. Nasrabadi. Kernel orthogonal subspace projection for hyperspectral signal classification［J］. IEEE Trans. Geoscience and Remote Sensing, 2005, 43(12): 2952～2962

[4] [4] L. Capobianco, G. Camps-Valls. Target detection with a contextual kernel orthogonal subspace projection［C］. SPIE, 2008, 7109: 71090D

[5] [5] Li Shanshan, Zhang Bing, Gao Lianru et al.. Research of hyperspectral target detection on alogirityms based on variance minimum [J]. Acta Optica Sinica, 2010, 30(7): 2116～2121

[6] [6] Kun Tan, Peijun Du. Combined multi-kernel support vector machine and wavelet analysis for hyperspectral remote sensing image classification［J］. Chin. Opt. Lett., 2011, 9(1): 011003

[7] [7] Wang Haihong, Zeng Ni, Lu Wei et al.. Edge detection of laser imaging radar based on wavelet transform and mathematical morphology［J］. Chinese J. Lasers, 2008, 35(6): 903～906

[8] [8] Li Na, Zhao Huijie, Jia Guorui et al.. Anomaly detection based on extended mathematical morphology for hyperspectral imagery［J］. Acta Optica Sinica, 2008, 28(8): 1480～1484

[9] [9] Zhao Liaoying, Zhang Kai, Li Xiaorun. Kernel signature space orthogonal projection for target detection in hyperspectral imagery［J］. J. Remote Sensing, 2011, 15(1): 13～28

[10] [10] Liu Sheng, Wang Xiaoyu, Qiu Xinfa. A mathematical morphology filtering algorithm for high-resolution remote sensing image［J］. Meteorology and Disaster Reduction Research, 2008, 31(4): 48～51

[11] [11] Duan Shan. Mathematical Morphology and its Application Research in Remote Sensing Image Processing［D］. Wuhan：Wuhan Univesity, 2004. 115～124

[12] [12] J. Shawe-Taylor, N. Cristianini. Kernel Methods for Pattern Analysis [M]. Zhao Linlin, Wen Suming, Zeng Huajun et al. Transl.. Beijing: China Machine Press, 2005. 20～42

[13] [13] W. Fan, B. Hu, J. Miller et al.. Comparative study between a new nonlinear model and common linear model for analysing laboratory simulated-forest hyperspectral data［J］. Int. J. Remote Sensing, 2009, 30(11): 2951～2962

[14] [14] R. N. Clark. Spectral library 06. USGS digital spectral Libraries [OL]. [2011-5-10]. http://speclab.cr.usgs.gov

[15] [15] Li Xiaorun, Wu Xiaoming, Zhao Liaoying. Unsupervised nonlinear decomposition method of hyperspectral imagery［J］. J. Zhejiang University( Engineering Science), 2011, 45(4): 607～613

[16] [16] US Army Corps of Engineers. Hypercube [OL]. [2011-10-24]. http://www.agc.army.mil/Hypercube/