[1] HYVRINEN A, KARHUNEN J, OJA E. Independent Component Analysis ［M］. New York: John Wiley & Sons, 2001.

[2] WANG J, CHANG CH I. Applications of independent component analysis in endmember extraction and abundance quantification for hyperspectral imagery ［J］.IEEE Transactions on Geoscience and Remote Sensing, 2006, 44(9): 2601-2616.

[3] CHANG CH I, JIAO X L, WU CH CH, et al.. Component analysis-based unsupervised linear spectral mixture analysis for hyperspectral imagery ［J］. IEEE Transactions on Geoscience and Remote Sensing, 2011, 49(11): 4123-4137.

[4] WANG J, CHANG CH I. Independent component analysis-based dimensionality reduction with applications in hyperspectral image analysis ［J］.IEEE Transactions on Geoscience and Remote Sensing, 2006, 44(6): 1586-1600.

[5] CHANG CH I. Hyperspectral Data Processing Algorithm Design and Analysis ［M］. New Jersey: John Wiley & Sons, 2013.

[6] DU P, ZHAO H J.Noise robust ICA feature extraction algorithm for hyperspectral image ［J］.Journal of Beijing University of Aeronautics and Astronautics, 2005, 31(10): 1101-1105. (in Chinese)

[7] FU X N, ZHANG T, WAN L. Smoke detection based on multispectral separation ［J］. Opt. Precision Eng., 2013, 21(11): 2798-2802. (in Chinese)

[8] QIN Y H, DING X Q, GONG H L. High dimensional feature selection in near infrared spectroscopy classification ［J］. Infrared and Laser Engineering, 2013, 42(5): 1355-1359. (in Chinese)

[9] LIU ZH G, LU Y L, WEI Y W. Supervised method for hyperspectral image camouflage target detection ［J］. Infrared and Laser Engineering, 2013, 42(11): 3076-3081. (in Chinese)

[10] LI P, WEI ZH H, HE X, et al.. Object recognition based on shape feature fusion under multi-views［J］. Opt. Precision Eng., 2014, 22(12): 3368-3376. (in Chinese)

[11] ZHENG SH G, ZHU N B, BAO Y, et at.. A modified fast independent component analysis and its application to image separation ［J］. Journal of Image and Graphics, 2003, 8(10): 1159-1165. (in Chinese)

[12] HUANG L Y, GAO Q, KANG H Y, et al.. Improved fast ICA algorithm ［J］. Journal of North China Electric Power University, 2006, 33 (3): 59-62. (in Chinese)

[13] JI C, YU Y, YU P. Improved algorithm for independent component analysis ［J］. Journal of Northeastern University (Natural Science), 2010, 8(8): 1086-1088. (in Chinese)

[14] YANG J A, ZHUANG ZH Q, WU B, et al.. An improved fast ICA algorithm based on negentropy maximization ［J］. 2002, 7(4): 37-40. (in Chinese)

[15] JI C, HU X N, ZHU L CH, et al.. Improved higher order convergent fast ICA algorithm ［J］. Journal of Northeastern University (Natural Science), 2011, 32(10): 1390-1393. (in Chinese)

[16] JI C, WANG Y R, SHA M B, et al.. Relaxation factor-based fast ICA with higher order convergence ［J］. Journal of Northeastern University (Natural Science), 2014, 35(2): 204-207. (in Chinese)

[17] GU Y F, WANG CH, WANG SH ZH, et al.. Kernel-based regularized-angle spectral matching for target detection in hyperspectral imagery ［J］.Pattern Recognition Letters, 2011, 32: 114-119.

[18] WANG ZH L, FENG Y, XIAO H, et al.. Distributed compressive sensing imaging and reconstruction of hyperspectral imagery ［J］. Opt. Precision Eng., 2015, 23(4): 1131-1137. (in Chinese)

[19] YIN Y N, WANG X D, LI B Y. Lossless compression method based on prediction and JPEG2000 for MODIS emissive IR bands multispectral image ［J］. Chinese Journal of Liquid Crystals and Displays, 2013, 28(6): 922-926. (in Chinese)

[20] ZHANG M X, GAO J B, MENG H M, et al.. Zoom-FFT based on fourier transform spectroscopy ［J］. Journal of Applied Optics, 2013, 34(3): 452-456. (in Chinese)

[21] LI Y, GAO J B, MENG H M, et al.. Fast inversion techniques of inteferogram imaging spectrum base on CUDA ［J］. Journal of Applied Optics, 2014, 35(3): 414-419. (in Chinese)