Binary division algorithm using a linear discriminant function for the cluster analysis of remotely sensed multispectral images

Hiroshi Hanaizumi; Shinji Chino; Sadao Fujimura

doi:10.1117/12.226832

17 November 1995 Binary division algorithm using a linear discriminant function for the cluster analysis of remotely sensed multispectral images

Hiroshi Hanaizumi, Shinji Chino, Sadao Fujimura

Author Affiliations +

Proceedings Volume 2579, Image and Signal Processing for Remote Sensing II; (1995) https://doi.org/10.1117/12.226832
Event: Satellite Remote Sensing II, 1995, Paris, France

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.

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Hiroshi Hanaizumi, Shinji Chino, and Sadao Fujimura "Binary division algorithm using a linear discriminant function for the cluster analysis of remotely sensed multispectral images", Proc. SPIE 2579, Image and Signal Processing for Remote Sensing II, (17 November 1995); https://doi.org/10.1117/12.226832

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