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Proceedings Paper

Binary division algorithm using a linear discriminant function for the cluster analysis of remotely sensed multispectral images
Author(s): Hiroshi Hanaizumi; Shinji Chino; Sadao Fujimura
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Paper Abstract

A new method is proposed for clustering remotely sensed multispectral images. This method has a binary division process in which division boundaries are determined by an algorithm of linear discriminant function. In order to realize high speed processing, image data are compressed and projected onto a 2D subspace. Then, the image data are repeatedly divided into groups until stopping conditions are satisfied. In this method, the optimal number of clusters are automatically determined accordingly to the statistical property of the image data. The method has higher speed than ISODATA does, and is successfully applied to actual multispectral images.

Paper Details

Date Published: 17 November 1995
PDF: 6 pages
Proc. SPIE 2579, Image and Signal Processing for Remote Sensing II, (17 November 1995); doi: 10.1117/12.226832
Show Author Affiliations
Hiroshi Hanaizumi, Hosei Univ. (Japan)
Shinji Chino, Hosei Univ. (Japan)
Sadao Fujimura, Univ. of Tokyo (Japan)

Published in SPIE Proceedings Vol. 2579:
Image and Signal Processing for Remote Sensing II
Jacky Desachy, Editor(s)

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