[1] 李德仁,童庆禧,李荣兴,等.高分辨率对地观测的若干前沿科学问题[J].中国科学:地球科学,2012,42(6):805-813. Li D R,Tong Q X,Li R X,et al.Current issues in high-resolution Earth observation technology[J].Science China Earth Sciences,2012,55(7):1043-4051.
[2] Chang C I.Hyperspectral Data Processing:Algorithm Design and Analysis[M].Hoboken,NJ,USA:John Wiley and Sons Inc,2013.
[3] Zhang L P,Huang X.Advanced processing techniques for remotely sensed imagery[J].Journal of Remote Sensing,2009,13(4):559-569.
[4] Rosin P L.Robust pixel unmixing[J].IEEE Transactions on Geoscience and Remote Sensing,2001,39(9):1978-1983.
[5] 普晗晔,王斌,张立明.基于单形体几何的高光谱遥感图像解混算法[J].中国科学:信息科学,2012,42(8):1019-1033. Pu H Y,Wang B,Zhang L M.Simplex geometry-based abundance estimation algorithm for hyperspectral unmixing[J].Scientia Sinica Informationis,2012,42(8):1019-1033.
[6] Wirasakti S,Zein R A,Mafazi F.Comparative study of land cover linear spectral mixture analysis(LSMA)model on multispectral and hyperspectral imagery[C]//34th Asian Conference on Remote Sensing.Bali,Indonesia:[s.n.],2013.
[7] 赵春晖,肖健钰.一种利用互信息加权的最小二乘法丰度反演算法[J].沈阳大学学报:自然科学版,2014,26(1):45-49. Zhao C H,Xiao J Y.An abundance inversion algorithm based on mutual information weighted least square error[J].Journal of Shenyang University:Natural Science,2014,26(1):45-49.
[8] 唐晓燕,高昆,倪国强.高光谱图像非线性解混方法的研究进展[J].遥感技术与应用,2013,28(4):731-738. Tang X Y,Gao K,Ni G Q.Nonlinear spectral unmixing of hyperspectral images[J].Remote Sensing Technology and Application,2013,28(4):731-738.
[9] Camps-Valls G,Bruzzone L.Kernel Methods for Remote Sensing Data Analysis[M].Chichester:John Wiley and Sons Ltd,2009.
[10] Hosseini S A,Ghassemian H.A new fast algorithm for multiclass hyperspectral image classification with SVM[J].International Journal of Remote Sensing,2011,32(23):8657-8683.
[11] Broadwater J,Banerjee A.Mapping intimate mixtures using an adaptive kernel-based technique[C]//Proceeding of the 3rd Workshop on Hyperspectral Image and Signal Processing:Evolution in Remote Sensing.Lisbon:IEEE,2011:1-4.
[12] 刘婷婷,林珲,张良培,等.利用SVM相关反馈和语义挖掘的遥感影像检索[J].武汉大学学报:信息科学版,2012,37(4):415-418. Liu T T,Lin H,Zhang L P,et al.SVM-relevance-feedback and semantic-extraction-based RS image retrieval[J].Geomatics and Information Science of Wuhan University,2012,37(4):415-418.
[13] 王晓飞,张钧萍,张晔.高光谱图像混合像元分解算法[J].红外与毫米波学报,2010,29(3):210-215,229. Wang X F,Zhang J P,Zhang Y.Unmixing algorithm of hyperspectral images[J].Journal of Infrared and Millimeter Waves,2010,29(3):210-215,229.
[14] 谭熊,余旭初,张鹏强,等.基于多核支持向量机的高光谱影像非线性混合像元分解[J].光学精密工程, 2014,22(7):1912-1920. Tan X,Yu X C,Zhang P Q,et al.Nonlinear mixed pixel decomposition of hyperspectral imagery based on multiple kernel SVM[J].Optics and Precision Engineering,2014,22(7):1912-1920.
[15] Kwon H,Nasrabadi N M.Kernel orthogonal subspace projection for hyperspectral signal classification[J].IEEE Transactions on Geoscience and Remote Sensing,2005,43(12):2952-2962.
[16] Liu K H,Wong E,Du E Y,et al.Kernel-based linear spectral mixture analysis[J].IEEE Geoscience and Remote Sensing Letters,2012,9(1):129-133.
[17] 王挺,杜博,张良培.顾及局域信息的核化正交子空间投影目标探测方法[J].武汉大学学报:信息科学版,2013,38(2):200-203,239. Wang T,Du B,Zhang L P.A local information-based kernelized OSP method for target detection[J].Geomatics and Information Science of Wuhan University,2013,38(2):200-203,239.
[18] 赵春晖,尤佳,李晓慧.基于自适应核方法的正交子空间投影异常检测算法[J].黑龙江大学自然科学学报,2012,29(2):254-258,272. Zhao C H,You J,Li X H.An orthogonal subspace projection anomaly detection algorithm based on adaptive kernel method[J].Journal of Natural Science of Heilongjiang University,2012,29(2):254-258,272.
[19] Bajorski P.Analytical comparison of the matched filter and orthogonal subspace projection detectors for hyperspectral images[J].IEEE Transactions on Geoscience and Remote Sensing,2007,45(7):2394-2402.
[20] Capobianco L,Garzelli A,Camps-Valls G.Target detection with semisupervised kernel orthogonal subspace projection[J].IEEE Transactions on Geoscience and Remote Sensing,2009,47(11):3822-3833.
[21] Fauvel M,Chanussot J,Benediktsson J A.Kernel principal component analysis for the classification of hyperspectral remote sensing data over urban areas[J].EURASIP Journal on Advances in Signal Processing,2009,2009:783194.
[22] 林娜,杨武年,王斌.高光谱遥感影像核最小噪声分离变换特征提取[J].武汉大学学报:信息科学版,2013,38(8):988-992. Lin N,Yang W N,Wang B.Hyperspectral image feature extraction via kernel minimum noise fraction transform[J].Geomatics and Information Science of Wuhan University,2013,38(8):988-992.
[23] Molero J M,Garzón E M,García I,et al.Anomaly detection based on a parallel kernel RX algorithm for multicore platforms[J].Journal of Applied Remote Sensing,2012,6(1):061503.
[24] Broadwater J,Chellappa R,Banerjee A,et al.Kernel fully constrained least squares abundance estimates[C]//Proceedings of IEEE International Geoscience and Remote Sensing Symposium.Barcelona,Spain:IEEE,2007:4041-4044.
[25] 林娜,杨武年,王斌.基于KMNF和BP神经网络的高光谱遥感影像分类[J].计算机工程与设计,2013,34(8):2774-2777,2782. Lin N,Yang W N,Wang B.Hyperspectral image classification on KMNF and BP neural network[J].Computer Engineering and Design,2013,34(8):2774-2777,2782.
[26] 林娜,杨武年,王斌.基于核最小噪声分离变换的高光谱遥感影像多类SVM分类[J].计算机应用与软件,2014,31(6):116-119. Lin N,Yang W N,Wang B.Multi-class SVM classification for hyperspectral remote sensing image based on kernel minimum noise fraction transform[J].Computer Applications and Software,2014,31(6):116-119.
[27] Swayze G A,Clark R N,Goetz A F H,et al.Mapping advanced argillic alteration at Cuprite,Nevada,using imaging spectroscopy[J].Economic Geology,2014,109(5):1179-1221.
[28] 林娜,杨武年,王斌.基于FLAASH的AVIRIS高光谱影像大气校正[J].地理空间信息,2013,11(4):49-50,54. Lin N,Yang W N,Wang B.Atmospheric correction of AVIRIS hyperspectral image based on FLAASH[J].Geospatial Information,2013,11(4):49-50,54. |