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Proceedings Paper

Unsupervised classification of changes in multispectral satellite imagery
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Paper Abstract

The statistical techniques of multivariate alteration detection, maximum autocorrelation factor transformation, expectation maximization, fuzzy maximum likelihood estimation and probabilistic label relaxation are combined in a unified scheme to classify changes in multispectral satellite data. An example involving bitemporal LANDSAT TM imagery is given.

Paper Details

Date Published: 10 November 2004
PDF: 8 pages
Proc. SPIE 5573, Image and Signal Processing for Remote Sensing X, (10 November 2004); doi: 10.1117/12.565090
Show Author Affiliations
Morton J. Canty, Forschungszentrum Julich (Germany)
Allan A. Nielsen, Technical Univ. of Denmark (Denmark)


Published in SPIE Proceedings Vol. 5573:
Image and Signal Processing for Remote Sensing X
Lorenzo Bruzzone, Editor(s)

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