[1] [1] ZHONG Y F,LI W Q,WANG X Y,et al.Satellite ground integrated destriping network:A new perpective for EO-1 hyperion and Chinese hyperspectral satellite datasets[J].Remote Sensing of Environment,2020,237:111416.

[3] [3] STUART M B,DAVIES M,HOBBS M J,et al.High resolution hyperspectral imaging using low costcom-ponents:Application within environmental monitoring scenarios[J].Sensors,2022,22(12):4652.

[4] [4] NI L,XU H G,ZHOU X M.Mineral identification and mapping by synthesis of hyperspectral VNIR/SWIR and multispectral TIR remotely sensed data with different classifiers[J].IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing,2020,13:3155-3163.

[5] [5] KANG X,XIANG X,LI S,et al.PCA-based edge-preserving features for hyperspectral image classification[J].IEEE Transactions on Geoscience & Remote Sensing,2017,55(12):1-12.

[6] [6] FABIYI S D,MURRAY P,ZABALZA J,et al.Folded LDA:extending the linear discriminant analysis algorithm for feature extraction and data reduction in hyperspectral remote sensing[J].IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing,2021,14:12312-12331.

[7] [7] NING Y N,PENG J T,SUN L,et al.Adaptive local discriminant analysis and distribution matching for domain adaptation in hyperspectral image classification[J].IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing,2022,15:4797-4808.

[8] [8] CHENG X Y,XU Y T,ZHANG J J,et al.Hyperspectral anomaly detection via low-rank decomposition and morphological filtering[J].IEEE Geoscience and Remote Sensing Letters,2021,19:1-5.

[9] [9] YE Z,FOWLER J E,BAI L.Spatial-spectral hyperspectral classification using local binary patterns and Markov random fields[J].Journal of Applied Remote Sensing,2017,11(3):035002.

[11] [11] LV H H,WANG Z L,ZHANG H.Edge protection filtering and convolutional neural network for hyper-spectral remote sensing image classification[J].Infrared Physics & Technology,2022,122:104039.

[14] [14] WANG A L,WANG Y,CHEN Y S.Hyperspectral image classification based on convolutional neural network and random forest[J].Remote Sensing Letters,2019,10(11):1086-1094.

[16] [16] GHANBARI H,HOMAYOUNI S,SAFARI A,et al.Gaussian mixture model and Markov random fields for hypers- pectral image classification[J].European Journal of Remote Sensing,2018,51(1):889-900.

[17] [17] CAI Y M,ZHANG Z J,YAN Q,et al.Densely connected convolutional extreme learning machine for hyperspectral image classification[J]. Neurocomputing,2021,434:21-32.

[18] [18] YUE J,ZHAO W,MAO S,et al.Spectral-spatial classification of hyperspectral images using deep convolutional neural networks[J].Remote Sensing Letters,2015,6(6):468-477.

[19] [19] LI Y,ZHANG H,SHEN Q.Spectral-spatial classification of hyperspectral imagery with 3D convolutional neural network[J].Remote Sensing,2017,9(1):67.

[20] [20] LI Z K,TANG X Y,LI W,et al.A two-stage deep domain adaptation method for hyperspectral image classification[J].Remote Sensing,2020,12(7):1054.

[21] [21] WU H J,LI D,WANG Y J,et al.Hyperspectral image classification based on two-branch spectral spatial feature attention network[J].Remote Sensing,2021,13(21):4262.

[22] [22] YAN H P,WANG J,TANG L,et al.A 3D cascaded spectral-spatial element attention network for hyper-spectral image classification[J].Remote Sensing,2021,13,2451.

[23] [23] LIU D X,HAN G L,LIU P X,et al.A novel 2D-3D CNN with spectral-spatial multi-scale feature fusion for hyperspectral image classification[J].Remote Sensing,2021,13(22):4621.

[25] [25] HUANG L,CHEN W Y,LIU Y G,et al.Improving neural machine translation using gated state network and focal adaptive attention networtk[J].Neural Computing and Applications,2021,33(23):15955-15967.

[27] [27] HUO Z Q,JIN H,QIAO Y X,et al.Deep high resolution network with double attention residual blocks for human pose estimation[J].IEEE Access, 2020, 8:224947-224957.

[30] [30] DING C,CHEN Y F,LI R Z,et al.Integrating hybrid pyramid feature fusion and coordinate attention for effective small sample hyperspectral image classification[J].Remote Sensing,2022,14(10):2355.