[1] David Landgrebe. Hyperspectral image data analysis[J]. IEEE Signal Processing Magazine, 2002, 19(1): 17～28
[3] S. M. Bergman. The utility of hyperspectral data to detect and discriminate actual and decoy target vehicles[R]. AD report A327453, 1996
[4] D. Stein, Jon Schoonmaker, Eric Coolbaugh. Hyperspectral imaging for intelligence, surveillance, and reconnaissance[R]. AD report A434124, 2001
[5] Capt Peterson Erin D. Surface and buried landmine scene generation and validation using the digital imaging and remote sensing image generation (DIRSIG) model[R]. AD report A424769, 2004
[6] Office of the Secretary of Defense, U. S. Department of Defense. Unmanned Aircraft Systems Roadmap 2005～2030[R]. 2005. 47～59
[7] X. L. Yu, I. S. Reed, A. D. Stocker. Comparative performance analysis of adaptive multispectral detectors[J]. IEEE Transactions on Signal Processing, 1993, 41(8): 2639～2656
[9] C. I. Chang, S. S. Chiang. Anomaly detection and classification for hyperspectral imagery[J]. IEEE Transactions on Geoscience and Remote Sensing, 2002, 40(6): 1314～1325
[10] Chein-I Chang, Shao-Shan Chiang, Irving W. Ginsberg. Anomaly detection in hyperspectral imagery[C]. Proc. SPIE, 2001, 4383: 43～50
[11] He Lin, Pan Quan, Zhao Yongqiang et al.. An automatic target detection algorithm for hyperspectral imagery based on feature-level fusion[C]. Proc. SPIE, 2005, 6043: 164～169
[14] T. M. Cover, J. A. Thomas. Elements of Information Theory[M]. New York: Wiley-Interscience Press, 1991. 266～278
[16] David B. Marden, Dimitris Manolakis. Modeling hyperspectral imaging data[C]. Proc. SPIE, 2003, 5093: 253～262
[17] Dimitris Manolakis, David Marden, John Kerekes et al.. On the statistics of hyperspectral imaging data[C]. Proc. SPIE, 2001, 4381: 308～316
[18] D. W. Scott. Multivariate density estimation and visualization. http:∥www.stat.rice.edu/～scottdw/multidens.ps
[19] B. A. Turlach. Bandwidth selection in kernel density estimation: A review. http:∥citeseer.ist.psu.edu/214125.html
