Fast Nearest Neighbor Classification Methods for Multispectral Imagery.
Nearest neighbor classifiers have not been widely used by remote sensing practitioners. The lack of acceptance of these classifiers may be partially due to their notoriously slow speed of execution which makes them impractical for the classification of mega-pixel images. However, training data reduc...
| Publicado en: | Professional Geographer Vol. 44; no. 2; pp. 191 - 203 |
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| Autores principales: | , |
| Formato: | Artículo |
| Publicado: |
Taylor & Francis Ltd
May1992
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| Materias: | |
| Acceso en línea: | Ver este registro en EBSCOhost |
| Sumario: | Nearest neighbor classifiers have not been widely used by remote sensing practitioners. The lack of acceptance of these classifiers may be partially due to their notoriously slow speed of execution which makes them impractical for the classification of mega-pixel images. However, training data reduction, distance measure optimization, and neighbor searching algorithms based on the modified k-d tree can speed nearest neighbor classification substantially. |
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