[2] [2] Reed I S, YU X. Adaptive multiple-band CFAR detection of an optical pattern with unknown spectral distribution[J]. IEEE Transactions on Acoustics Speech & Signal Processing, 1990, 38(10): 1760-1770.

[3] [3] Ashton E A, Schaum A. Algorithms for the detection of sub-pixel targets in multispectral imagery[J]. Photogrammetric Engineering & Remote Sensing, 1998, 64(7): 723-731.

[4] [4] Taitano Y, Geier B, Bauer K. A locally adaptable iterative RX detector[J].EURASIP Journal on Advances in Signal Processing, 2010, 2010(1):341908.

[5] [5] Molero J M, Garzón E M, García I, et al. Analysis and optimizations of global and local versions of the RX algorithm for anomaly detection in hyperspectral data[J]. IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing, 2013, 6(2): 801-814.

[6] [6] Kwon H, Nasrabadi N M. Kernel RX-algorithm: a nonlinear anomaly detector for hyperspectral imagery[J]. IEEE Transactions on Geoscience and Remote Sensing, 2005, 43(2): 388-397.

[8] [8] CHEN Yi, Nasrabadi N M, Tran T D. Sparse representation for target detection in hyperspectral imagery[J]. IEEE Journal of Selected Topics in Signal Processing, 2011, 5(3): 629-640.

[9] [9] SUN Weiwei, LIU Chun, LI Jialin, et al. Low-rank and sparse matrix decomposition-based anomaly detection for hyperspectral imagery[J].Journal of Applied Remote Sensing, 2014, 8(1): 083641.

[10] [10] XU Yang, WU Zebin, LI Jun, et al. Anomaly detection in hyperspectral images based on low-rank and sparse representation[J]. IEEE Transactions on Geoscience & Remote Sensing, 2016, 54(4): 1990-2000.

[11] [11] LI Wei , DU Qian. Collaborative representation for hyperspectral anomaly detection[J]. IEEE Transactions on Geoscience and Remote Sensing,2015, 53(3): 1463-1474.

[13] [13] Itti L, Koch C, Niebur E. A model of saliency-based visual attention for rapid scene analysis[J]. IEEE Transactions on Pattern Analysis and Machine Intelligence, 1998, 20(11): 1254-1259.

[14] [14] LIANG Jie, ZHOU Jun, BAI Xiao, et al. Salient object detection in hyperspectral imagery[C]//IEEE International Conference on Image Processing, 2014: 2393-2397.

[15] [15] CAO Yan, ZHANG Jing, TIAN Qi, et al. Salient target detection in hyperspectral images using spectral saliency[C]//IEEE China Summit and International Conference on Signal and Information Processing, 2015:1086-1090.

[17] [17] ZHAO Minghua, YUE Liqin, HU Jing, et al. Salient target detection in hyperspectral image based on visual attention[J/OL]. IET Image Processing, 2021, 15(11): https://doi.org/10.1049/ipr2.12197.

[18] [18] XIANG Pei, SONG Jiangluqi, QIN Hanlin, et al. Visual attention and background subtraction with adaptive weight for hyperspectral anomaly detection[J]. IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing, 2021, 14: 2270-2283.

[19] [19] ZHU Wei, LIU Jian, ZHU Mingyue, et al. Research on improved algorithm of DR image enhancement based on Gauss-Laplacian pyramid[J]. Chinese Journal of Medical Instrumentation, 2019, 43(1): 10-13.

[21] [21] WANG Qi, ZHANG Fahong, LI Xuelong. Optimal clustering framework for hyperspectral band selection[J]. IEEE Transactions on Geoscience and Remote Sensing, 2018, 56(10): 5910-5922.

[25] [25] KANG Xudong, ZHANG Xiangping, LI Shutao , et al. Hyperspectral anomaly detection with attribute and edge-preserving filters[J]. IEEE Transactions on Geoscience and Remote Sensing, 2017(10): 1-12.