HYPERSPECTRAL REMOTE SENSING IMAGE CLASSIFICATION BASED ON SUPPORT VECTOR MACHINE

[in Chinese]; [in Chinese]

[1] Lothar Hermes,Dieter Frieau,Jan Puzicha,et al.Support Vector Machines for Land Usage Classification in Landsat TM Imagery[J].In:Proc.IGARSS'99,1:348-350.

[2] Huang C,Davis L S.Townshend J R G.An assessment of support vector machines for land cover classification[J].International Journal of Remote Sensing,2002,23:725-749.

[3] Martin Brown,Hugh G Lewis,Steve R Gunn.Linear Spectral Mixture Models and Support Vector Machines for Remote Sensing[J].IEEE Transactions on Geoscience and Remote Sensing,2000,38(5):2346-2360.

[5] Zhang J,Zhang Y,Zhou T.Classification of hyperspectral data using support vector machine[C].In:IEEE International Conference on Image Processing,2001:882-885.

[7] Vapnik V N.Statistical Learning Theory[M].New York:Wiley.1998.

[8] Kre el U.Pairwise Classification and Support Vector Machines[M].In Advances in Kernel Methods:Support Vector Learning,B.Scholkopf,C.J.C.Burges,and A.J.Smola (eds.),The MIT Press,Cambridge,MA,1999:255-268.

[9] Hsu C W,Lin C J.A comparison of methods for multi-class support vector machines[J].IEEE Transactions on Neural Networks,2002,13(2):415-425,2002.

[10] Boardman J W,Kruse F A.Automated spectral analysis:a geological example using AVIRIS data,north Grapevine Mountains[C].Nevada:In Proceeding,ERIM Tenth Thematic Conference on Geologic Remote Sensing,Environmental Research Institute of Michigan,Ann Arbor,MI,1994,I-407-I-418.