References
- AVIRIS, 1992, NW Indiana's Indian Pines 1992 data set. Available online at: ftp://ftp.ecn.purdue.edu/biehl/MultiSpec/92AV3C.lan (original files) and ftp://ftp.ecn.purdue.edu/biehl/PC_MultiSpec/ThyFiles.zip (ground truth)
- Bar-Hillel , A. , Hertz , T. , Shental , N. and Weinshall , D. 2005 . Learning a Mahalanobis distance from equivalence constraints . Journal of Machine Learning Research , 6 : 937 – 965 .
- Camps-Valls , G. , Gomez-Chova , L. , Munoz-Mari , J. , Vila-Frances , J. and Calpe-Maravilla , J. 2006 . Composite kernels for hyperspectral image classification . IEEE Geoscience and Remote Sensing Letters , 3 : 93 – 97 .
- Goldberger , J. , Roweis , S. , Hinton , G. and Salkhutdinov , R. 2004 . Neighbourhood components analysis . Advances in Neural Information Processing Systems (NIPS) , 17 : 513 – 520 .
- Kou , B. C. and Landgrebe , D. A. 2004 . Nonparametric weighted feature extraction for classification . IEEE Transactions on Geoscience and Remote Sensing , 42 : 1096 – 1105 .
- Kou , B. C. and Chang , K. Y. 2007 . Feature extraction for sample size classification problem . IEEE Transactions on Geoscience and Remote Sensing , 45 : 756 – 764 .
- Lee , C. and Landgrebe , D. A. 1993 . Feature extraction based on decision boundaries . IEEE Transactions Pattern Analysis and Machine Intelligence , 15 : 388 – 400 .
- Melgani , F. and Bruzzone , L. 2004 . Classification of hyperspectral remote sensing images with support vector machines . IEEE Transactions on Geoscience and Remote Sensing , 42 : 1778 – 1796 .
- Schölkopf , B. and Smola , A. 2001 . Learning with Kernels Support Vector Machines, Regularization, Optimization and Beyond , Cambridge, MA : MIT Press .