[5] [5] Bioucas-Dias J M, Plaza A, Camps-Valls G, et al. Hyperspectral remote sensing data analysis and future challenges[J]. IEEE Geoscience and Remote Sensing Magazine, 2013, 1(2): 6-36.

[6] [6] Gao L, Han Z, Hong D, et al. CyCU-Net: cycle-consistency unmixing network by learning cascaded autoencoders[J]. IEEE Transactions on Geoscience and Remote Sensing, 2021, 60: 5503914.

[7] [7] Drumetz L, Meyer T R, Chanussot J, et al. Hyperspectral image unmixing with endmember bundles and group sparsity inducing mixed norms[J]. IEEE Transactions on Image Processing, 2019, 28(7): 3435-3450.

[8] [8] Heinz D C, Chein-I-Chang. Fully constrained least squares linear spectral mixture analysis method for material quantification in hyperspectral imagery[J]. IEEE Transactions on Geoscience and Remote Sensing, 2001, 39(3): 529-545.

[9] [9] Zhuang L, Lin C H, Figueiredo M A T, et al. Regularization parameter selection in minimum volume hyperspectral unmixing[J]. IEEE Transactions on Geoscience and Remote Sensing, 2019, 57(12): 9858-9877.

[10] [10] Rasti B, Koirala B, Scheunders P, et al. UnDIP: hyperspectral unmixing using deep image prior[J]. IEEE Transactions on Geoscience and Remote Sensing, 2021, 60: 5504615.

[11] [11] Qu Y, Qi H. uDAS: an untied denoising autoencoder with sparsity for spectral unmixing[J]. IEEE Transactions on Geoscience and Remote Sensing, 2019, 57(3): 1698-1712.

[12] [12] Palsson B, Ulfarsson M O, Sveinsson J R. Convolutional autoencoder for spectral-spatial hyperspectral unmixing[J]. IEEE Transactions on Geoscience and Remote Sensing, 2021, 59(1): 535-549.

[13] [13] Ghosh P, Roy S K, Koirala B, et al. Hyperspectral unmixing using transformer network[J]. IEEE Transactions on Geoscience and Remote Sensing, 2022, 60: 5535116.

[14] [14] Wang Y, Chen X, Zhao E, et al. An unsupervised momentum contrastive learning based transformer network for hyperspectral target detection[J]. IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing, 2024, 17: 9053-9068.

[15] [15] Zhu F, Wang Y, Fan B, et al. Spectral unmixing via data-guided sparsity[J]. IEEE Transactions on Image Processing, 2014, 23(12): 5412-5427.

[16] [16] Schaepman M E, Jehle M, Hueni A, et al. Advanced radiometry measurements and Earth science applications with the Airborne Prism Experiment (APEX)[J]. Remote Sensing of Environment, 2015, 158: 207-219.