[1] 鲍蕊, 薛朝辉, 张像源, 等.综合聚类和上下文特征的高光谱影像分类[J].武汉大学学报·信息科学版, 2017, 42(7):890-896 http://ch.whu.edu.cn/CN/Y2017/V42/I7/890

Bao Rui, Xue Zhaohui, Zhang Xiangyuan, et al. Classification Merged with Clustering and Context for Hyperspectral Imagery[J]. Geomatics and Information Science of Wuhan University, 2017, 42(7):890-896 http://ch.whu.edu.cn/CN/Y2017/V42/I7/890
[2] Jiang Xinwei, Song Xin, Zhang Yongshan, et al. Laplacian Regularized Spatial-Aware Collaborative Graph for Discriminant Analysis of Hyperspectral Imagery[J]. Remote Sensing, 2019, 11(1):29 doi:  10.3390/rs11010029
[3] Jiang Junjun, Ma Jiayi, Chen Chen, et al. SuperPCA:A Superpixel Wise Principal Component Analysis Approach for Unsupervised Feature Extraction of Hyperspectral Imagery[J]. IEEE Transactions on Geoscience & Remote Sensing, 2018, 56(8):4581-4593 doi:  10.1109/TGRS.2018.2828029
[4] Chen Zhikun, Jiang Junjun, Jiang Xinwei, et al. Spectral-Spatial Feature Extraction of Hyper-spectral Images Based on Propagation Filter[J]. Sensors, 2018, 18(6), doi:10. 3390/s/18061978
[5] Ma Jiayi, Jiang Junjun, Zhou Huabing, et al. Guided Locality Preserving Feature Matching for Remote Sensing Image Registration[J]. IEEE Transactions on Geoscience and Remote Sensing, 2018, 56(8):4581-4593 doi:  10.1109/TGRS.2018.2828029
[6] Jiang Junjun, Ma Jiayi, Wang Zheng, et al. Hyperspectral Image Classification in the Presence of Noisy Labels[J]. IEEE Transactions on Geoscience and Remote Sensing, 2018, 99:1-15 doi:  10.1109/TGRS.2018.2861992
[7] Jiang Xinwei, Fang Xiaoping, Chen Zhikun, et al. Supervised Gaussian Process Latent Variable Model for Hyperspectral Image Classification[J]. IEEE Geoscience and Remote Sensing Letters, 2017, 14(10):1760-1764 doi:  10.1109/LGRS.2017.2734680
[8] 王毅, 李季.基于SVM的高光谱遥感图像亚像元定位[J].武汉大学学报·信息科学版, 2017, 42(2):198-201 http://ch.whu.edu.cn/CN/Y2017/V42/I2/198

Wang Yi, Li Ji. Sub-pixel Mapping Based on SVM of Hyperspectral Remotely Sensed Imagery[J]. Geomatics and Information Science of Wuhan University, 2017, 42(2):198-201 http://ch.whu.edu.cn/CN/Y2017/V42/I2/198
[9] 孙伟伟, 蒋曼, 李巍岳.利用稀疏自表达实现高光谱影像波段选择[J].武汉大学学报·信息科学版, 2017, 42(4):441-448 http://ch.whu.edu.cn/CN/Y2017/V42/I4/441

Sun Weiwei, Jiang Man, Li Weiyue. Band Selection Using Sparse Self-representation for Hyperspectral Imagery[J]. Geomatics and Information Science of Wuhan University, 2017, 42(4):441-448 http://ch.whu.edu.cn/CN/Y2017/V42/I4/441
[10] 刘英, 吴立新, 岳辉.基于梯度结构相似度的矿区土壤湿度空间分析[J].武汉大学学报·信息科学版, 2018, 43(1):87-93 http://ch.whu.edu.cn/CN/Y2018/V43/I1/87

Liu Ying, Wu Lixin, Yue Hui. Spatial Distribution Characteristics Analysis of Soil Moisture in Desertification Mining Areas Based on Gradient-Based Structural Similarity[J]. Geomatics and Information Science of Wuhan University, 2018, 43(1):87-93 http://ch.whu.edu.cn/CN/Y2018/V43/I1/87
[11] 姚玲, 刘高焕, 刘庆生, 等.利用影像分类分析黄河三角洲人工刺槐林健康[J].武汉大学学报·信息科学版, 2010, 35(7):863-867 http://ch.whu.edu.cn/CN/Y2010/V35/I7/863

Yao Ling, Liu Gaohuan, Liu Qingsheng, et al. Remote Sensing Monitoring the Health of Artificial Robinia Pseudoacacia Forest[J]. Geomatics and Information Science of Wuhan University, 2010, 35(7):863-867 http://ch.whu.edu.cn/CN/Y2010/V35/I7/863
[12] 赵波, 苏红军, 蔡悦.一种切空间协同表示的高光谱遥感影像分类方法[J].武汉大学学报·信息科学版, 2018, 43(4):555-562 http://ch.whu.edu.cn/CN/Y2018/V43/I4/555

Zhao Bo, Su Hongjun, Cai Yue. A Hyperspectral Image Classification Method Based on Collaborative Representation in Tangent Space[J]. Geomatics and Information Science of Wuhan University, 2018, 43(4):555-562 http://ch.whu.edu.cn/CN/Y2018/V43/I4/555
[13] Jiang Junjun, Chen Chen, Yu Yi, et al. Spatial-Aware Collaborative Representation for Hyperspectral Remote Sensing Image Classification[J]. IEEE Geoscience & Remote Sensing Letters, 2017, 4(3):404-408 http://www.wanfangdata.com.cn/details/detail.do?_type=perio&id=79a06f9ab845aeef5dd8479268559cb5
[14] Li Wei, Chen Chen, Su Hongjun, et al. Local Binary Patterns and Extreme Learning Machine for Hyperspectral Imagery Classification[J]. IEEE Transactions on Geoscience and Remote Sensing, 2015, 53(7):3681-3693 doi:  10.1109/TGRS.2014.2381602
[15] Pan Bin, Shi Zhenwei, Xu Xia. Hierarchical Guidance Filtering-Based Ensemble Classification for Hyperspectral Images[J]. IEEE Transactions on Geoscience and Remote Sensing, 2017, 55(7):4177-4189 doi:  10.1109/TGRS.2017.2689805
[16] Zhou Yicong, Wei Yantao. Learning Hierarchical Spectral-Spatial Features for Hyperspectral Image Classification[J]. IEEE Transactions on Cybernetics, 2016, 46(7):1667-1678 doi:  10.1109/TCYB.2015.2453359
[17] Chen Zhikun, Jiang Junjun, Zhou Chong. Trilateral Smooth Filtering for Hyperspectral Image Feature Extraction[J]. IEEE Geoscience and Remote Sensing Letters, 2019, 16(5):781-785 doi:  10.1109/LGRS.2018.2881704
[18] 张建廷, 张立民.结合光谱和纹理的高分辨率遥感图像分水岭分割[J].武汉大学学报·信息科学版, 2017, 42(4):449-455, 467 http://ch.whu.edu.cn/CN/Y2017/V42/I4/449

Zhang Jianting, Zhang Limin. A Watershed Algorithm Combining Spectral and Texture Information for High Resolution Remote Sensing Image Segmentation[J]. Geomatics and Information Science of Wuhan University, 2017, 42(4):449-455, 467 http://ch.whu.edu.cn/CN/Y2017/V42/I4/449
[19] Kang Xundong, Li Shutao, Benediktsson J A. Spectral-Spatial Hyperspectral Image Classification with Edge-Preserving Filtering[J]. IEEE Transactions on Geoscience & Remote Sensing, 2014, 52(5):2666-2677 http://d.old.wanfangdata.com.cn/Periodical/zdhxb201802008
[20] Chen Zhikun, Jiang Junjun, Zhou Chong, et al. SuperBF:Superpixel-Based Bilateral Filtering Algorithm and Its Application in Feature Extraction of Hyperspectral Images[J]. IEEE Access, 2019, 7:147796-147807 doi:  10.1109/ACCESS.2019.2938397
[21] 白璘, 刘盼芝, 惠萌.利用小波核最小噪声分离进行高光谱影像SVM分类[J].武汉大学学报·信息科学版, 2016, 41(5):624-628, 644 http://ch.whu.edu.cn/CN/Y2016/V41/I5/624

Bai Lin, Liu Panzhi, Hui Meng. SVM Classification of Hyperspectral Image Based on Wavelet Kernel Minimum Noise Fraction[J]. Geomatics and Information Science of Wuhan University, 2016, 41(5):624-628, 644 http://ch.whu.edu.cn/CN/Y2016/V41/I5/624
[22] Chang C C, Lin C J. LIBSVM:A Library for Support Vector Machines[J]. ACM Transactions on Intelligent Systems and Technology, 2011, doi:10. 1145/1961189. 1961199