[1] [1] Liu Xiaogang, Zhao Huijie, Li Na. Feature extraction based on multifractal spectrum for hyperspectral data［J］. Acta Optica Sinica, 2009, 29(3): 844～848

[2] [2] He Lin, Pan Quan, Di Wei et al.. Research advance on target detection for hyperspectral imagery［J］. Acta Electronica Sinica, 2009, 37(9): 2016～2024

[3] [3] Li Shanshan, Zhang Bing, Gao Lianru et al.. Research of hyperspectral target detection algorithms based on variance minimum［J］. Acta Optica Sinica, 2010, 30(7): 2116～2122

[4] [4] Li Na, Zhao Huijie, Jia Guorui et al.. Anomaly detection based on extended mathematical morphology for hyperectral imagery［J］. Acta Optica Sinica, 2008, 28(8): 1480～1484

[5] [5] Y. F. Gu, C. Wang, S. Z. Wan et al.. Kernel-based regularized-angle spectral matching for target detection in hyperspectral imagery［J］. Pattern Recognition Letters, 2011, 32(2): 114～119

[6] [6] Xun Lina, Fang Yonghua, Li Xin. A small target detection approach based on endmember extraction in hyperspectral image［J］. Acta Optica Sinica, 2007, 27(7): 1178～1182

[7] [7] Han Ling, Dong Lianfeng, Zhang Min et al.. Destriping hyperspectral image based on an improved moment matching method［J］. Acta Optica Sinica, 2009, 29(12): 3333～3338

[8] [8] I. S. Reed, X. L. Yu. Adaptive multiple-band CFAR detection of an optical pattern with unknown spectral distribution［J］. IEEE Transactions on Acoustics, Speech, and Signal Processing, 1990, 38(10): 1760～1766

[9] [9] He Lin, Pan Quan, Di Wei et al.. A small-target detector based on single likelihood test for hyperspectral imagery［J］. Acta Optica Sinica, 2007, 27(12): 2155～2162

[10] [10] S. Matteoli, M. Diani, G. Corsini. A tutorial overview of anomaly detection in hyperspectral images［J］. IEEE Aerospace and Electronic Systems Magazine, 2010, 25(7): 5～27

[11] [11] H. Kwon, N. M. Nasrabadi. Kernel RX-algorithm: a nonlinear anomaly detector for hyperspectral imagery［J］. IEEE Transactions on Geoscience and Remote Sensing, 2005, 43(2): 388～397

[12] [12] S. S. Chiang, C. I. Chang, I. W. Ginsberg. Unsupervised target detection in hyperspectral images using projection pursuit［J］. IEEE Transactions on Geoscience and Remote Sensing, 2001, 39(7): 1380～1391

[13] [13] Li Zhiyong, Kuang Gangyao, Zou Huanxin. Application of project pursuit in hyperspectral anomaly detection［J］. Journal of Electronics & Information Technology, 2004, 26(9): 1474～1479

[14] [14] Chen Mi, Yi Yaohua, Li Deren et al.. Application of projection pursuit based on dynamical evolutionary algorithm to anomaly target detection in hyperspectral images［J］. Geomatics and Information Science of Wuhan University, 2006, 31(1): 55～58

[15] [15] Lu Wei, Yu Xuchu, Liu Juan et al.. A small targets detection approach based on anomaly distributing in hyperspectral imagery［J］. Acta Geodaetica et Cartogr aphica Sinica, 2006, 35(1): 40～45

[16] [16] J. A. Malpica, J. G. Rejas, M. C. Alonso. A projection pursuit algorithm for anomaly detection in hyperspectral imagery［J］. Pattern Recognition, 2008, 41(11): 3313～3327

[17] [17] J. Kennedy, R. C. Eberhart. Particle swarm optimization［C］. Perth: IEEE International Conference on Neural Networks, 1995. 1942～1948

[18] [18] Liu Chunhong, Zhao Chunhui, Zhang Linyan. A new method of hyperspectral remote sensing image dimensional reduction［J］. Journal of Image and Graphics, 2005, 10(2): 218～222

[19] [19] J. H. Friedman, J. W. Tukey. A projection pursuit algorithm for exploratory data analysis［J］. IEEE Transactions on Computer, 1974, 23(9): 881～890

[20] [20] Meng Hongji, Zheng Peng, Mei Guohui et al.. Particle swarm optimization algorithm based on chaotic series［J］. Control and Decision, 2006, 21(3): 263～266