Classification of hyperspectral remote sensing images with support vector machines

作者: F. Melgani , L. Bruzzone

DOI: 10.1109/TGRS.2004.831865

关键词:

摘要: … problem of the classification of hyperspectral remote sensing data using support vector machines. In order to assess the effectiveness of this promising classification methodology, we …

参考文章(47)
F. Melgani, L. Bruzzone, Support vector machines for classification of hyperspectral remote-sensing images international geoscience and remote sensing symposium. ,vol. 1, pp. 506- 508 ,(2002) , 10.1109/IGARSS.2002.1025088
Keinosuke Fukunaga, Introduction to statistical pattern recognition (2nd ed.) Academic Press Professional, Inc.. ,(1990)
Joseph T. Morgan, Alex Henneguelle, Melba M. Crawford, Joydeep Ghosh, Amy Neuenschwander, Adaptive Feature Spaces for Land Cover Classification with Limited Ground Truth Data multiple classifier systems. pp. 189- 200 ,(2002) , 10.1007/3-540-45428-4_19
Philip H. Swain, Hans Hauska, The decision tree classifier: Design and potential IEEE Transactions on Geoscience and Remote Sensing. ,vol. 15, pp. 142- 147 ,(1977) , 10.1109/TGE.1977.6498972
T.K. Moon, The expectation-maximization algorithm IEEE Signal Processing Magazine. ,vol. 13, pp. 47- 60 ,(1996) , 10.1109/79.543975
M. G. Kendall, H. O. Lancaster, A Course in the Geometry of n Dimensions ,(2004)
P. Pudil, J. Novovičová, J. Kittler, Floating search methods in feature selection Pattern Recognition Letters. ,vol. 15, pp. 1119- 1125 ,(1994) , 10.1016/0167-8655(94)90127-9
B.M. Shahshahani, D.A. Landgrebe, The effect of unlabeled samples in reducing the small sample size problem and mitigating the Hughes phenomenon international geoscience and remote sensing symposium. ,vol. 32, pp. 1087- 1095 ,(1994) , 10.1109/36.312897
L. Bruzzone, F. Roli, S.B. Serpico, An extension of the Jeffreys-Matusita distance to multiclass cases for feature selection IEEE Transactions on Geoscience and Remote Sensing. ,vol. 33, pp. 1318- 1321 ,(1995) , 10.1109/36.477187
A. P. Dempster, N. M. Laird, D. B. Rubin, Maximum Likelihood from Incomplete Data Via theEMAlgorithm Journal of the Royal Statistical Society: Series B (Methodological). ,vol. 39, pp. 1- 22 ,(1977) , 10.1111/J.2517-6161.1977.TB01600.X