[1] Bioucas-Dias J M, Plaza A, Dobigeon N, et al. Hyperspectral unmixing overview:geometrical, statistical, and sparse regression-based approaches[J]. IEEE Journal of Selected Topics in Applied Earth Observations Remote Sensing, 2012, 5(2):354-379.
[2] Dobigeon N, Tourneret J Y, Cdric Richard, et al. Nonlinear unmixing of hyperspectral images:Models and algorithms[J]. IEEE Signal Processing Magazine, 2013, 31(1):82-94.
[3] Keshava N, Mustard J F. Spectral unmixing[J]. Signal Processing Magazine IEEE, 2002, 19(1):44-57.
[4] Hape B. Bidirectional reflectance spectroscopy:I. theory[J]. Journal of Geophysical Research:Solid Earth, 1981, 86(B4):3039-3045.
[5] Borel C C, Saw G. Nonlinear spectral mixing models for vegetative and soil surfaces[J]. Remote Sensing of Environment, 1994, 47(3):403-416.
[6] Shkuratov Y, Starukhina L, Hoffmann H, et al. A model of spectral albedo of particulate surfaces:implications for optical properties of the moon[J]. Icarus, 1999, 137(2):235-246.
[7] Hapke B. Theory of Reflectance and Emittance Spectroscopy[M]. New York:Cambridge University Press, 1993.
[8] Chen Lei, Guo Yanju, Ge Baozhen. Nonlinear unmixing of hyperspectral images based on differential search algorithm[J]. Chinese Journal of Electronics, 2017, 45(2):337-345.(in Chinese)陈雷, 郭艳菊, 葛宝臻. 基于微分搜索的高光谱图像非线性解混算法[J]. 电子学报, 2017, 45(2):337-345.
[9] Fan W Y, Hu B X, Miller J, et al. Comparative study between a new nonlinear model and common linear model for analysing laboratory simulated-forest hyperspectral data[J]. International Journal of Remote Sensing, 2009, 30(11):2951-2962.
[10] Halimi A, Altmann Y, Dobigeon N, et al. Nonlinear unmixing of hyperspectral images using a generalized bilinear model[J]. IEEE Transactions on Geoscience Remote Sensing, 2011, 49(11):4153-4162.
[11] Altmann Y, Halimi A, Dobigeon N, et al. Supervised nonlinear spectral unmixing using a polynomial post nonlinear model for hyperspectral imagery[C]//IEEE International Conference on Acoustics, Speech and Signal Processing. IEEE, 2011:1009-1012.
[12] Marinoni A, Gamba P. Accurate detection of anthropogenic settlements in hyperspectral images by higher order nonlinear unmixing[J]. IEEE Journal of Selected Topics in Applied Earth Observations Remote Sensing, 2017, 9(5):1792-1801.
[13] Heylen R, Scheunders P. A Multilinear mixing model for nonlinear spectral unmixing[J]. IEEE Transactions on Geoscience Remote Sensing, 2016, 54(1):240-251.
[14] Zhu F, Halimi A, Honeine P, et al. Correntropy maximization via ADMM:application to robust hyperspectral unmixing[J]. IEEE Transactions on Geoscience Remote Sensing, 2017, 55(9):4944-4955.
[15] Zelinski A C, Goyal V K. Denoising hyperspectral imagery and recovering junk bands using wavelets and sparse approximation[C]//IEEE International Conference on Geoscience and Remote Sensing Symposium, 2006:387-390.
[16] Zhu F Y, Wang Y, Fan B, et al. Spectral unmixing via data-guided sparsity[J]. IEEE Trans Image Process, 2014, 23(12):5412-5427.
[17] Lu X, Wu H, Yuan Y, et al. Manifold regularized sparse NMF for hyperspectral unmixing[J]. IEEE Transactions on Geoscience Remote Sensing, 2013, 51(5):2815-2826.
[18] Chen Lei, Gan Shizhong, Sun Qian. Nonlinear unmixing using backtracking optimization for hyperspectral imagery[J]. Infrared and Laser Engineering, 2017, 46(6):0638001. (in Chinese)陈雷, 甘士忠, 孙茜. 基于回溯优化的非线性高光谱图像解混[J]. 红外与激光工程, 2017, 46(6):0638001.
[19] Civicioglu P. Transforming geocentric cartesian coordinates to geodetic coordinates by using differential search algorithm[J]. Computers Geosciences, 2012, 46(3):229-247.
[20] Wang Y, Cai Z, Zhang Q. Differential evolution with composite trial vector generation strategies and control parameters[J]. IEEE Transactions on Evolutionary Computation, 2011, 15(1):55-66.
[21] Karaboga D and Basturk B. On the performance of artificial bee colony (ABC) algorithm[J]. Applied Soft Computing, 2008, 8(1):687-697.
[22] Daz A, Rios A, Barron J, et al. An automatic document classifier system based on genetic algorithm and taxonomy[J]. IEEE Access, 2018, 6:21552-21559.
[23] Nascimento J M and Dias J M. Vertex component analysis:A fast algorithm to unmix hyperspectral data[J]. IEEE Transactions on Geoscience and Remote Sensing, 2005, 43(4):898-910.