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...

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Bibliographic Details
Published in:Professional Geographer Vol. 44; no. 2; pp. 191 - 203
Main Authors: Hardin, Perry J., Thomson, Curtis N.
Format: Article
Published: Taylor & Francis Ltd May1992
Subjects:
Online Access:View this record in EBSCOhost
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        atl: Fast Nearest Neighbor Classification Methods for Multispectral Imagery.
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          Hardin, Perry J.
          Thomson, Curtis N.
        affil:
          Brigham Young University
          University of Idaho
      su:
        Remote-sensing images
        Remote sensing
        Mathematical optimization
        Algorithms
        Space telescopes
      sug:
        subj:
          Remote-sensing images
          Remote sensing
          Mathematical optimization
          Algorithms
          Space telescopes
      keyword:
        distance measure optimization
        hierarchical structures
        nearest neighbor classifier
      ab: 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.
      pubtype: Academic Journal
      doctype: Article
      src: R
    language: English
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