[1] Li J X, Zheng K, Yao J et al. Deep unsupervised blind hyperspectral and multispectral data fusion[J]. IEEE Geoscience and Remote Sensing Letters, 19, 6007305(2022).
[2] Hughes G. On the mean accuracy of statistical pattern recognizers[J]. IEEE Transactions on Information Theory, 14, 55-63(1968).
[3] Agarwal A, El-Ghazawi T, El-Askary H et al. Efficient hierarchical-PCA dimension reduction for hyperspectral imagery[C], 353-356(2008).
[4] Wang J, Chang C I. Independent component analysis-based dimensionality reduction with applications in hyperspectral image analysis[J]. IEEE Transactions on Geoscience and Remote Sensing, 44, 1586-1600(2006).
[5] Jia S, Qian Y T, Li J M et al. Feature extraction and selection hybrid algorithm for hyperspectral imagery classification[C], 72-75(2010).
[6] Lu Y S, Li Y X, Liu B et al. Hyperspectral data haze monitoring based on deep residual network[J]. Acta Optica Sinica, 37, 1128001(2017).
[7] Wu C, Wu Y Q. Target detection in hyperspectral image using projection pursuit based on chaotic particle swarm optimization[J]. Acta Optica Sinica, 31, 1211003(2011).
[8] Wang D G, Rao W Q, Sun X et al. Siamese network with pixel-pair for hyperspectral image anomaly detection[J]. Journal of Image and Graphics, 26, 1860-1870(2021).
[9] Sun W W, Zhang L P, Du B et al. Band selection using improved sparse subspace clustering for hyperspectral imagery classification[J]. IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing, 8, 2784-2797(2015).
[10] Li S J, Qi H R. Sparse representation based band selection for hyperspectral images[C], 2693-2696(2011).
[11] Cai Y M, Liu X B, Cai Z H. BS-nets: an end-to-end framework for band selection of hyperspectral image[J]. IEEE Transactions on Geoscience and Remote Sensing, 58, 1969-1984(2020).
[12] Guan S H, Yang G, Lu S et al. Multi-objective optimization of hyperspectral band selection based on attention mechanism[J]. Acta Optica Sinica, 40, 2128002(2020).
[13] Su H J, Du Q, Chen G S et al. Optimized hyperspectral band selection using particle swarm optimization[J]. IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing, 7, 2659-2670(2014).
[14] Su H J, Yong B, Du Q. Hyperspectral band selection using improved firefly algorithm[J]. IEEE Geoscience and Remote Sensing Letters, 13, 68-72(2016).
[15] Zhang W Q. Research on unsupervised hyperspectral band selection based on vector subspace projection[D](2020).
[16] Chang C I, Du Q, Sun T L et al. A joint band prioritization and band-decorrelation approach to band selection for hyperspectral image classification[J]. IEEE Transactions on Geoscience and Remote Sensing, 37, 2631-2641(1999).
[17] Su H J, Yang H, Du Q et al. Semisupervised band clustering for dimensionality reduction of hyperspectral imagery[J]. IEEE Geoscience and Remote Sensing Letters, 8, 1135-1139(2011).
[18] Wang Q, Zhang F H, Li X L. Optimal clustering framework for hyperspectral band selection[J]. IEEE Transactions on Geoscience and Remote Sensing, 56, 5910-5922(2018).
[19] Martinez-Uso A, Pla F, Sotoca J M et al. Clustering-based hyperspectral band selection using information measures[J]. IEEE Transactions on Geoscience and Remote Sensing, 45, 4158-4171(2007).
[20] Qian Y, Yao F, Jia S. Band selection for hyperspectral imagery using affinity propagation[J]. IET Computer Vision, 3, 213-222(2009).
[21] Su H J, Sheng Y H, Du P J et al. Adaptive affinity propagation with spectral angle mapper for semi-supervised hyperspectral band selection[J]. Applied Optics, 51, 2656-2663(2012).
[22] Yang R L, Su L F, Zhao X B et al. Representative band selection for hyperspectral image classification[J]. Journal of Visual Communication and Image Representation, 48, 396-403(2017).
[23] Yuan Y, Lin J Z, Wang Q. Dual-clustering-based hyperspectral band selection by contextual analysis[J]. IEEE Transactions on Geoscience and Remote Sensing, 54, 1431-1445(2016).
[24] Bezdek J C, Ehrlich R, Full W. FCM: The fuzzy c-means clustering algorithm[J]. Computers & Geosciences, 10, 191-203(1984).
[25] Yang X S. Firefly algorithms for multimodal optimization[M]. Watanabe O, Zeugmann T. Stochastic algorithms: foundations and applications. Lecture notes in computer science, 5792, 169-178(2009).
[26] Zhang Q K. Research on the particle swarm optimization and differential evolution algorithms[D](2017).
[27] Cai Y M, Zhang Z J, Liu X B et al. Efficient graph convolutional self-representation for band selection of hyperspectral image[J]. IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing, 13, 4869-4880(2020).