[1] Cai L H, Ding J L. Inversion of soil moisture content based on hyperspectral multi-scale decomposition[J]. Laser & Optoelectronics Progress, 55, 013001(2018).

[2] Shaw G. D. Signal processing for hyperspectral image exploitation[J]. IEEE Signal Processing Magazine, 19, 12-16(2002). http://ieeexplore.ieee.org/document/974715

[3] Zhang B, Zhuang L N, Gao L R et al. PSO-EM: a hyperspectral unmixing algorithm based on normal compositional model[J]. IEEE Transactions on Geoscience and Remote Sensing, 52, 7782-7792(2014).

[4] Du J, Hu B L, Zhang Z F. Gastric carcinoma classification based on convolutional neural network and micro-hyperspectral imaging[J]. Acta Optica Sinica, 38, 0617001(2018).

[5] Matsuki T, Yokoya N, Iwasaki A. Hyperspectral tree species classification of Japanese complex mixed forest with the aid of lidar data[J]. IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing, 8, 2177-2187(2015). http://ieeexplore.ieee.org/document/7085996

[6] Zeng C P, Ju L J, Zhang J C. Hyperspectral image classification based onclustering dimensionality reduction and visual attention mechanism[J]. Laser & Optoelectronics Progress, 56, 212802(2019).

[7] Song Y G, Wu Z B, Wei Z H et al. Survey of sparsity constrained hyperspectral unmixing[J]. Journal of Nanjing University of Science and Technology, 37, 486-492(2013).

[8] Nascimento J M P, Dias J M B. Vertex component analysis: a fast algorithm to unmix hyperspectral data[J]. IEEE Transactions on Geoscience and Remote Sensing, 43, 898-910(2005).

[9] Hendrix E M T, Garcia I, Plaza J et al. A new minimum-volume enclosing algorithm for endmember identification and abundance estimation in hyperspectral data[J]. IEEE Transactions on Geoscience and Remote Sensing, 50, 2744-2757(2012).

[10] Chan T H, Chi C Y, Huang Y M et al. A convex analysis-based minimum-volume enclosing simplex algorithm for hyperspectral unmixing[J]. IEEE Transactions on Signal Processing, 57, 4418-4432(2009).

[11] Miao LD, Qi H R. Endmember extraction from highly mixed data using minimum volume constrained nonnegative matrix factorization[J]. IEEE Transactions on Geoscience and Remote Sensing, 45, 765-777(2007).

[12] Li J, Agathos A, Zaharie D et al. Minimum volume simplex analysis:a fast algorithm for linear hyperspectral unmixing[J]. IEEE Transactions on Geoscience and Remote Sensing, 53, 5067-5082(2015).

[13] Zhuang L N, Lin CH. Figueiredo M A T, et al. Regularization parameter selection in minimum volume hyperspectral unmixing[J]. IEEE Transactions on Geoscience and Remote Sensing, 57, 9858-9877(2019).

[14] Li J. Bioucas-Dias J M, Plaza A, et al. Robust collaborative nonnegative matrix factorization for hyperspectral unmixing[J]. IEEE Transactions on Geoscience and Remote Sensing, 54, 6076-6090(2016).

[15] Feng X R, Li H C, Li J et al. Hyperspectral unmixing using sparsity-constrained deep nonnegative matrix factorization with total variation[J]. IEEE Transactions on Geoscience and Remote Sensing, 56, 6245-6257(2018).

[16] Xiong F C, Qian Y T, Zhou J et al. Hyperspectral unmixing via total variation regularized nonnegative tensor factorization[J]. IEEE Transactions on Geoscience and Remote Sensing, 57, 2341-2357(2019).

[17] Zhang X R, Sun Y J, Zhang J Y et al. Hyperspectral unmixing via deep convolutional neural networks[J]. IEEE Geoscience and Remote Sensing Letters, 15, 1755-1759(2018).

[18] Craig M D. Minimum-volume transforms for remotely sensed data[J]. IEEE Transactions on Geoscience and Remote Sensing, 1994, 32(3): 542-552.[J]. IEEE Access, 7, 186352-186363(2019).

[19] Iordache M D. Bioucas-Dias J M, Plaza A. Sparse unmixing of hyperspectral data[J]. IEEE Transactions on Geoscience and Remote Sensing, 49, 2014-2039(2011).

[20] Bruckstein A M, Elad M, Zibulevsky M. On the uniqueness of nonnegative sparse solutions to underdetermined systems of equations[J]. IEEE Transactions on Information Theory, 54, 4813-4820(2008).

[21] Boyd S, Parikh N, Chu E et al. Distributed optimization and statistical learning via the alternating direction method of multipliers[J]. Foundations & Trends in Machine Learning, 3, 1-122(2010).

[22] Lin CH, Ma F, Chi C Y et al. A convex optimization-based coupled nonnegative matrix factorization algorithm for hyperspectral and multispectral data fusion[J]. IEEE Transactions on Geoscience and Remote Sensing, 56, 1652-1667(2018).

[23] Iordache M D. Bioucas-Dias J M, Plaza A. Total variation spatial regularization for sparse hyperspectral unmixing[J]. IEEE Transactions on Geoscience and Remote Sensing, 50, 4484-4502(2012).

[24] Clark R, Swayze G, Wise R et al. 2020-04-14]. http:∥speclab.cr.usgs.gov/spectral.lib06.(2007).

[25] Qin J, Li H L, Chi J T et al. Fast blind hyperspectral unmixing based on graph Laplacian. [C]∥ 2019 10th Workshop on Hyperspectral Imaging and Signal Processing: Evolution in Remote Sensing (WHISPERS), September 24-26, 2019, Amsterdam, Netherlands. New York: IEEE, 1-5(2019).