[1] [1] Hughes G. On the mean accuracy of statistical pattern recognizers［J］. IEEE Transactions on Information Theory, 1968, 14(1): 55-63.

[2] [2] Zhang L P, Zhang L F. Hyperspectral remote sensing ［M］. Beijing: Surveying and Mapping Press, 2011: 71-74.

[3] [3] Frey B J, Dueck D. Clustering by passing messages between data points［J］. Science, 2007, 315(5814): 972-976.

[4] [4] Xia C M, Ni Z W, Ni L P, et al. Affinity propagation clustering algorithm based on density adjustment and manifold distance［J］. Computer Science, 2017, 44(10): 187-192, 215.

[5] [5] Chang C I. Spectral information divergence for hyperspectral image analysis［C］. IEEE 1999 International Geoscience and Remote Sensing Symposium, 1999: 6409333.

[6] [6] Zhao C H, Tian M H, Li J W. Research progress on spectral similarity metrics［J］. Journal of Harbin Engineering University, 2017, 38(8): 1179-1189.

[7] [7] Angelopoulou E, Lee S W, Bajcsy R. Spectral gradient: a material descriptor invariant to geometry and incident illumination［C］. Proceedings of the Seventh IEEE international Conference on Computer Vision, 1999: 861.

[8] [8] Zhang X B, Yuan Y, Jing J J, et al. Spectral discrimination method information divergence combined with gradient angle［J］. Spectroscopy and Spectral Analysis, 2011, 31(3): 853-857.

[9] [9] Wu H, Xu Y J, Gao R. Extraction of alteration information from hyperspectral imagery based on SCA and SID［J］. Geography and Geo-Information Science, 2016, 32(1): 44-48.

[10] [10] Liu X S, Ge L, Wang B, et al. An unsupervised band selection algorithm for hyperspectral imagery based on maximal information［J］. Journal of Infrared and Millimeter Waves, 2012, 31(2): 166-170, 176.

[11] [11] Liu C H, Zhao C H, Zhang L Y. A new method of hyperspectral remote sensing image dimensional reduction［J］. Journal of Image and Graphics, 2005, 10(2): 218-222.