BOUNDARY BASED SUPERVISED CLASSIFICATION OF HYPERSPECTRAL IMAGES WITH LIMITED TRAINING SAMPLES
One of the most important and challenging problems in supervised classification of high dimensional data is limited available training samples. Using the parametric classifiers is not appropriate in this condition. Thus a new simple nonparametric supervised classifier based boundary samples of each...
Main Authors: | M. Imani, H. Ghassemian |
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Format: | Article |
Language: | English |
Published: |
Copernicus Publications
2013-09-01
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Series: | The International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences |
Online Access: | http://www.int-arch-photogramm-remote-sens-spatial-inf-sci.net/XL-1-W3/203/2013/isprsarchives-XL-1-W3-203-2013.pdf |
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