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Proceedings Paper

Supervised classifier based on linear statistical interclass model and maximum likelihood decision
Author(s): Tetsuya Yuasa; Jaideep Kumar Mishra; Dikdik Setia Permana; Takanori Nakajima; Takao Akatsuka
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Paper Abstract

In this paper, we introduce a linear statistical model for an multispectral image segmentation to simultaneously describe not only interband but also interclass properties. Since the number of parameters to be estimated is reduced compared with the conventional maximum likelihood classifier based on multidimensional normal distributions, it is expected that reliable classification results will be achievable even from a restricted number of training data. We demonstrate the effectiveness of our classifier by applying it to simulated and actual satellite data.

Paper Details

Date Published: 17 July 2000
PDF: 7 pages
Proc. SPIE 4044, Hybrid Image and Signal Processing VII, (17 July 2000); doi: 10.1117/12.391927
Show Author Affiliations
Tetsuya Yuasa, Yamagata Univ. (Japan)
Jaideep Kumar Mishra, Yamagata Univ. (Japan)
Dikdik Setia Permana, Yamagata Univ. (Japan)
Takanori Nakajima, Yamagata Univ. (Japan)
Takao Akatsuka, Yamagata Univ. (Japan)

Published in SPIE Proceedings Vol. 4044:
Hybrid Image and Signal Processing VII
David P. Casasent; Andrew G. Tescher, Editor(s)

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