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Proceedings Paper

Knowledge-Based Multi-Spectral Image Classification
Author(s): Mark J. Carlotto; Victor T. Tom; Paul W. Baim; Richard A. Upton
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Paper Abstract

A new approach to the problem of classifying surface materials in satellite multi-spectral imagery is described and demonstrated in this paper. Surface material classes are defined heuristically using rules which describe the typical appearance of the material under specified conditions in terms of relative image measures. A knowledge-based approach allows expert knowledge of the domain to be used directly to develop classification rules. An expert system is currently being developed in the Zetalisp/Flavors programming environment on the Symbolics 3600 Lisp Machine. An example of its use in classifying Landsat Thematic Mapper imagery is presented.

Paper Details

Date Published: 4 December 1984
PDF: 9 pages
Proc. SPIE 0504, Applications of Digital Image Processing VII, (4 December 1984); doi: 10.1117/12.944845
Show Author Affiliations
Mark J. Carlotto, The Analytic Sciences Corp. (United States)
Victor T. Tom, The Analytic Sciences Corp. (United States)
Paul W. Baim, The Analytic Sciences Corp. (United States)
Richard A. Upton, The Analytic Sciences Corp. (United States)

Published in SPIE Proceedings Vol. 0504:
Applications of Digital Image Processing VII
Andrew G. Tescher, Editor(s)

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