Jackson Q,Landgrebe D A.An adaptive classifier design for high-dimensional data analysis with a limited training data set[J].IEEE Transactions on Geoscience and Remote Sensing,2001,39(12):2664-2679.
Kaufman Y J.Fraster R S.Atmospheric effect on classification of finite fields[J].Remote Sensing of Environment,1984,15(2):95-118.
[4]
Cracknell A P,Hayes L W.Atmospheric corrections to passive satellite remote sensing data[M]//Cracknell A P,Hayes L W B.Chapter 8 in Introduction to Remote Sensing.London:Taylor and Francis,1993:116-158.
[5]
Camps V G,Bandos T,Zhou D Y.Semi-supervised graph based hyperspectral image classification[J].IEEE Transaction on Geoscience and Remote Sensing,2007,45(10):3044-3054.
[6]
Du Y,Teillet P M,Cihlar J.Radiometric normalization of multitemporal high-resolution satellite images with quality control for land cover change detection[J].Remote Sensing of Environment,2002,82(1):123-134.
[7]
张友水, 冯学智,周成虎.多时相TM影像相对辐射校正研究[J].测绘学报,2006,35(2):122-127. Zhang Y S,Feng X Z,Zhou C H.Relative radiometric correction for multitemporal TM images[J].Acta Geodaetica et Cartographica Sinica,2006,35(2):122-127.
[8]
Koukal T,Suppan F,Schneider W.The impact of relative radiometric calibration on the accuracy of KNN-predictions of forest attributes[J].Remote Sensing of Environment,2007,110(4):431-437.
[9]
Ren G B,Zhang J,Ma Y,et al.A method for classification training sample spatial-time expanding of remote sensing images[C]//International Conference on Space Information Technology,Beijing,Proceedings of the SPIE,2009:76510G1-G7.
[10]
Scudder I I.Probability of error of some adaptive pattern-recognition machines[J].IEEE Transactions on Information Theory,1965,11(3):363-371.
[11]
Fralick S.Learning to recognize patterns without a teacher[J].IEEE Transactions on Information Theory,1967,13(1):57-64.
[12]
Nigam K,McCallum A,Mitchell T.Semi-supervised text classification using EM semi-supervised learning[M].Cambridge MA:MIT Press,2006:33-55.
[13]
István N T,Richárd F,János C.On positive and unlabeled learning for text classification[C]//István N T,Richárd F,János C.Lecture Notes in Computer Science.London:Springer,2011,6836:219-226.
[14]
Schenker A,Bunke H,Last M,et al.A graph-based framework for web document mining[M]//Schenker A,Bunke H,Last M,et al.Document Analysis Systems.London:Springer,2004:401-412.
[15]
Yang Y,Wu F,Nie F,et al.Web and personal image annotation by mining label correlation with relaxed visual graph embedding image processing[J].IEEE Transactions,2012,21(3):1339-1351.
[16]
Shahshahani B M,Landgrebe D A.The effect of unlabeled samples in reducing the small sample size problem and mitigating the hughes phenomenon[J].IEEE Transactions on Geoscience and Remote Sensing,1994,32(5):1087-1092.
[17]
骆剑承,王钦敏,马江洪,等.遥感图像最大似然分类方法的EM改进算法[J].测绘学报,2002,31(3):234-239. Luo J C,Wang Q M,Ma J H,et al.The EM-based maximum likelihood classifier for remotely sensed data[J].Acta Geodaetica et Cartographica Sinica,2002,31(3):234-239.
[18]
Tuia D,Camps V G.Semi-supervised remote sensing image classification with cluster kernels[J].IEEE Geoscience and Remote Sensing Letters,2009,6(2):224-228.
[19]
任广波,张杰,马毅,等.生成模型学习的遥感影像半监督分类[J].遥感学报,2010,14(6):1090-1104. Ren G B,Zhang J,Ma Y,et al.Generative model based semi-supervised learning method of remote sensing image classification[J].Journal of Remote Sensing,2010,14(6):1090-1104.
[20]
Tuia D,Pasolli E,Emery W J. Using active learning to adapt remote sensing image classifiers[J].Remote Sensing of Environment,2011,115(9):2232-2242.
[21]
Galante N,Siqueia R,Sant’Anna S J,et al.Semi-supervised remote sensing image classification methods assessment[C]//IGARSS. Geoscience and Remote Sensing Symposium.Vancouve:IEEE International,2011:2939-2942.
[22]
Mishra N S,Ghosh S,Ghosh A.Semi-supervised fuzzy clustering algorithms for change detection in remote sensing images[C]//Mishra N S,Ghosh S,Ghosh A.Lecture Notes in Computer Science.London:Springer,2012,7143:269-276.
[23]
Joachims T.Transductive inference for text classification using support vector machines[C]//Proceedings of the 16th International Conference on Machine Learning(ICML).San Francisco:Morgan Kaufmann Publishers,1999:200-209.
[24]
陈毅松,汪国平,董士海.基于支持向量机的渐进直推式分类学习算法[J].软件学报,2003,14(3):451-460. Chen Y S,Wang G P,Dong S H.A progressive transductive inference algorithm based on support vector machine[J].Journal of Software,2003,14(3):451-460.
[25]
沈新宇,许宏丽,官腾飞.基于直推式支持向量机的图像分类算法[J].计算机应用,2007,27(6):1463-1464. Shen X Y,Xu H L,Guan T F.Image classification based on transductive support vector machines[J].Computer Application,2007,27(6):1463-1464.
[26]
廖东平,魏玺章,黎湘,等.一种改进的渐进直推式支持向量机分类学习算法[J].信号处理,2008,24(2):213-218. Liao D P,Wei X Z,Li X,et al.An improved learning algorithm with progressive transductive support vector machine[J].Signal Processing,2008,24(2):213-218.
