"[1] KUO B C, LANDGREBE D A. A Robust Classification Procedure Based on Mixture Classifiers and Nonparametric Weighted Feature Extraction[J]. IEEE Transactions on Geoscience and Remote Sensing, 2002, 40(11): 2486-2494.
[2] LEE C, LANDGREBE D A. Feature Extraction Based on Decision Boundaries[J]. IEEE Transactions on Pattern Analysis and Machine Intelligence, 1993, 15(4): 388-400.
[3] LIU Chunhong, ZHAO Chunhui, ZHANG Lingyan. A New Method of Hyperspectral Remote Sensing Image Dimensional Reduction[J]. Journal of Image and Graphics, 2005, 10(2): 218-222. (刘春红, 赵春晖, 张凌雁. 一种新的高光谱遥感图像降维方法[J]. 中国图象图形学报, 2005, 10(2): 218-222.)
[4] LUO Jiancheng, ZHOU Chenghu, LIANG Yi, et al. Support Vector Machine for Spatial Feature Extraction and Classification of Remotely Sensed Imagery[J]. Journal of Remote Sensing, 2002, 6(1): 50-55. (骆剑承, 周成虎, 梁怡, 等. 支撑向量机及其遥感影像空间特征提取和分类的应用研究[J]. 遥感学报, 2002, 6(1): 50-55.)
[5] WANG Junshu, JIANG Nan, ZHANG Guoming, et al. Semi-supervised Classification Algorithm for Hyperspectral Remote Sensing Image Based on DE-self-training[J]. Transactions of the Chinese Society for Agricultural Machinery, 2015, 46(5): 239-244. (王俊淑, 江南, 张国明, 等. 高光谱遥感图像DE-self-training半监督分类算法[J]. 农业机械学报, 2015, 46(5): 239-244.)
[6] ZHOU Zhihua, ZHAN Dechuan, YANG Qiang. Semi-supervised Learning with Very Few Labeled Training Examples[C]//Proceedings of the National Conference on Artificial Intelligence. Cambridge, MA London: [s.n.], 2007, 22(1): 675-680.
[7] CHAWLA N V, KARAKOULAS G. Learning from Labeled and Unlabeled Data: An Empirical Study across Techniques and Domains[J]. Journal of Artificial Intelligence Research, 2005, 23(1): 331-366.
[8] LI Yuanqing, GUAN Cuntai, LI Huiqi, et al. A Self-training Semi-supervised SVM Algorithm and Its Application in an EEG-based Brain Computer Interface Speller System[J]. Pattern Recognition Letters, 2008, 29(9): 1285-1294.
[9] TAN Kun, DU Peijun. Wavelet Support Vector Machines Based on Reproducing Kernel Hilbert Space for Hyperspectral Remote Sensing Image Classification[J]. Acta Geodaetica et Cartographica Sinica, 2011, 40(2): 142-147. (谭琨, 杜培军. 基于再生核Hilbert空间的小波核函数支持向量机的高光谱遥感影像分类[J]. 测绘学报, 2011, 40(2): 142-147.)
[10] MELGANI F, BRUZZONE L. Classifcation of Hyperspectral Remote Sensing Images with Support Vector Machines[J]. IEEE Transactions on Geoscience and Remote Sensing, 2004, 42(8): 1778-1790.
[11] MANTHIRA MOORTHI S, MISRA I, KAUR R, et al. Kernel Based Learning Approach for Satellite Image Classification Using Support Vector Machine[C]//IEEE Recent Advances in Intelligent Computational Systems (RAICS). Trivandrum: IEEE, 2011: 107-110.
[12] DELL'ACQUA F, GAMBA P, FERRARI A, et al. Exploiting Spectral and Spatial Information in Hyperspectral Urban Data with High Resolution[J]. IEEE Geoscience and Remote Sensing Letters, 2004, 1(4): 322-326.
[13] LIANG Liang, YANG Minhua, LI Yingfang. Hyperspectral Remote Sensing Image Classification Based on ICA and SVM Algorithm[J]. Spectroscopy and Spectral Analysis, 2010, 30(10): 2724-2728. (梁亮, 杨敏华, 李英芳. 基于ICA与SVM算法的高光谱遥感影像分类[J]. 光谱学与光谱分析, 2010, 30(10): 2724-2728.)
[14] WU Jian. PENG Daoli. Vegetation Classification Technology of Hyperspectral Remote Sensing Based on Spatial Information[J]. Transactions of the Chinese Society of Agricultural Engineering, 2012, 28(5): 150-153. (吴见, 彭道黎. 基于空间信息的高光谱遥感植被分类技术[J]. 农业工程学报, 2012, 28(5): 150-153.)
[15] GAO Hengzhen, WAN Jianwei, WANG Libao, et al. Research on Classification Technique for Hyperspectral Imagery Based on Spectral-spatial Composite Kernels[J]. Signal Processing, 2011, 27(5): 648-652. (高恒振, 万建伟, 王力宝, 等. 基于谱域-空域组合核函数的高光谱图像分类技术研究[J]. 信号处理, 2011, 27(5): 648-652.)
[16] CHEN Shanjing, HU Yihua, SHI Liang, et al. Classification of Hyperspectral Imagery Based on Ant Colony Compositely Optimizing SVM in Spatial and Spectral Features[J]. Spectroscopy and Spectral Analysis, 2013, 33(8): 2192-2197. (陈善静, 胡以华, 石亮, 等. 空-谱二维蚁群组合优化SVM 的高光谱图像分类[J]. 光谱学与光谱分析, 2013, 33(8): 2192-2197.)
[17] POGGI G, SCARPA G, ZERUBIA J B. Supervised Segmentation of Remote Sensing Images Based on a Tree-structure MRF Model[J]. IEEE Transactions on Geoscience and Remote Sensing, 2005, 43(8): 1901-1911.
[18] JACKSON Q, LANDGREBE D A. Adaptive Bayesian Contextual Classification Based on Markov Random Fields[J]. IEEE Transactions on Geoscience and Remote Sensing, 2002, 40(11): 2454-2463.
[19] FAUVEL M, BENEDIKTSSON J A, CHANUSSOT J, et al. Spectral and Spatial Classification of Hyperspectral Data Using SVMs and Morphological Profiles[J]. IEEE Transactions on Geoscience and Remote Sensing, 2008, 46(11): 3804-3814.
[20] CRESPO J, SERRA J, SCHAFER R W. Theoretical Aspects of Morphological Filters by Reconstruction[J], Signal Processing, 1995, 47(2): 201-225.
[21] FAUVEL M, TARABALKA Y, BENEDIKTSSON J A, et al. Advances in Spectral-spatial Classification of Hyperspectral Images[J]. Proceedings of the IEEE, 2013, 101(3): 652-675.
[22] CHANG C C, LIN C J. LIBSVM: A Library for Support Vector Machines[J]. ACM Transactions on Intelligent Systems and Technology (TIST), 2011, 2(3): 27."
[1] KUO B C, LANDGREBE D A. A Robust Classification Procedure Based on Mixture Classifiers and Nonparametric Weighted Feature Extraction[J]. IEEE Transactions on Geoscience and Remote Sensing, 2002, 40(11): 2486-2494.
[2] LEE C, LANDGREBE D A. Feature Extraction Based on Decision Boundaries[J]. IEEE Transactions on Pattern Analysis and Machine Intelligence, 1993, 15(4): 388-400.
[3] LIU Chunhong, ZHAO Chunhui, ZHANG Lingyan. A New Method of Hyperspectral Remote Sensing Image Dimensional Reduction[J]. Journal of Image and Graphics, 2005, 10(2): 218-222. (刘春红, 赵春晖, 张凌雁. 一种新的高光谱遥感图像降维方法[J]. 中国图象图形学报, 2005, 10(2): 218-222.)
[4] LUO Jiancheng, ZHOU Chenghu, LIANG Yi, et al. Support Vector Machine for Spatial Feature Extraction and Classification of Remotely Sensed Imagery[J]. Journal of Remote Sensing, 2002, 6(1): 50-55. (骆剑承, 周成虎, 梁怡, 等. 支撑向量机及其遥感影像空间特征提取和分类的应用研究[J]. 遥感学报, 2002, 6(1): 50-55.)
[5] WANG Junshu, JIANG Nan, ZHANG Guoming, et al. Semi-supervised Classification Algorithm for Hyperspectral Remote Sensing Image Based on DE-self-training[J]. Transactions of the Chinese Society for Agricultural Machinery, 2015, 46(5): 239-244. (王俊淑, 江南, 张国明, 等. 高光谱遥感图像DE-self-training半监督分类算法[J]. 农业机械学报, 2015, 46(5): 239-244.)
[6] ZHOU Zhihua, ZHAN Dechuan, YANG Qiang. Semi-supervised Learning with Very Few Labeled Training Examples[C]//Proceedings of the National Conference on Artificial Intelligence. Cambridge, MA London: [s.n.], 2007, 22(1): 675-680.
[7] CHAWLA N V, KARAKOULAS G. Learning from Labeled and Unlabeled Data: An Empirical Study across Techniques and Domains[J]. Journal of Artificial Intelligence Research, 2005, 23(1): 331-366.
[8] LI Yuanqing, GUAN Cuntai, LI Huiqi, et al. A Self-training Semi-supervised SVM Algorithm and Its Application in an EEG-based Brain Computer Interface Speller System[J]. Pattern Recognition Letters, 2008, 29(9): 1285-1294.
[9] TAN Kun, DU Peijun. Wavelet Support Vector Machines Based on Reproducing Kernel Hilbert Space for Hyperspectral Remote Sensing Image Classification[J]. Acta Geodaetica et Cartographica Sinica, 2011, 40(2): 142-147. (谭琨, 杜培军. 基于再生核Hilbert空间的小波核函数支持向量机的高光谱遥感影像分类[J]. 测绘学报, 2011, 40(2): 142-147.)
[10] MELGANI F, BRUZZONE L. Classifcation of Hyperspectral Remote Sensing Images with Support Vector Machines[J]. IEEE Transactions on Geoscience and Remote Sensing, 2004, 42(8): 1778-1790.
[11] MANTHIRA MOORTHI S, MISRA I, KAUR R, et al. Kernel Based Learning Approach for Satellite Image Classification Using Support Vector Machine[C]//IEEE Recent Advances in Intelligent Computational Systems (RAICS). Trivandrum: IEEE, 2011: 107-110.
[12] DELL'ACQUA F, GAMBA P, FERRARI A, et al. Exploiting Spectral and Spatial Information in Hyperspectral Urban Data with High Resolution[J]. IEEE Geoscience and Remote Sensing Letters, 2004, 1(4): 322-326.
[13] LIANG Liang, YANG Minhua, LI Yingfang. Hyperspectral Remote Sensing Image Classification Based on ICA and SVM Algorithm[J]. Spectroscopy and Spectral Analysis, 2010, 30(10): 2724-2728. (梁亮, 杨敏华, 李英芳. 基于ICA与SVM算法的高光谱遥感影像分类[J]. 光谱学与光谱分析, 2010, 30(10): 2724-2728.)
[14] WU Jian. PENG Daoli. Vegetation Classification Technology of Hyperspectral Remote Sensing Based on Spatial Information[J]. Transactions of the Chinese Society of Agricultural Engineering, 2012, 28(5): 150-153. (吴见, 彭道黎. 基于空间信息的高光谱遥感植被分类技术[J]. 农业工程学报, 2012, 28(5): 150-153.)
[15] GAO Hengzhen, WAN Jianwei, WANG Libao, et al. Research on Classification Technique for Hyperspectral Imagery Based on Spectral-spatial Composite Kernels[J]. Signal Processing, 2011, 27(5): 648-652. (高恒振, 万建伟, 王力宝, 等. 基于谱域-空域组合核函数的高光谱图像分类技术研究[J]. 信号处理, 2011, 27(5): 648-652.)
[16] CHEN Shanjing, HU Yihua, SHI Liang, et al. Classification of Hyperspectral Imagery Based on Ant Colony Compositely Optimizing SVM in Spatial and Spectral Features[J]. Spectroscopy and Spectral Analysis, 2013, 33(8): 2192-2197. (陈善静, 胡以华, 石亮, 等. 空-谱二维蚁群组合优化SVM 的高光谱图像分类[J]. 光谱学与光谱分析, 2013, 33(8): 2192-2197.)
[17] POGGI G, SCARPA G, ZERUBIA J B. Supervised Segmentation of Remote Sensing Images Based on a Tree-structure MRF Model[J]. IEEE Transactions on Geoscience and Remote Sensing, 2005, 43(8): 1901-1911.
[18] JACKSON Q, LANDGREBE D A. Adaptive Bayesian Contextual Classification Based on Markov Random Fields[J]. IEEE Transactions on Geoscience and Remote Sensing, 2002, 40(11): 2454-2463.
[19] FAUVEL M, BENEDIKTSSON J A, CHANUSSOT J, et al. Spectral and Spatial Classification of Hyperspectral Data Using SVMs and Morphological Profiles[J]. IEEE Transactions on Geoscience and Remote Sensing, 2008, 46(11): 3804-3814.
[20] CRESPO J, SERRA J, SCHAFER R W. Theoretical Aspects of Morphological Filters by Reconstruction[J], Signal Processing, 1995, 47(2): 201-225.
[21] FAUVEL M, TARABALKA Y, BENEDIKTSSON J A, et al. Advances in Spectral-spatial Classification of Hyperspectral Images[J]. Proceedings of the IEEE, 2013, 101(3): 652-675.
[22] CHANG C C, LIN C J. LIBSVM: A Library for Support Vector Machines[J]. ACM Transactions on Intelligent Systems and Technology (TIST), 2011, 2(3): 27.
