Visualization and unsupervised classification of changes in multispectral satellite imagery
The statistical techniques of multivariate alteration detection, minimum/maximum autocorrelation factors transformation, expectation maximization and probabilistic label relaxation are combined in a unified scheme to visualize and to classify changes in multispectral satellite data. The methods are demonstrated with an example involving bitemporal LANDSAT TM imagery.
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Document Type: Research Article
Affiliations: 1: Forschungszentrum Jülich, D‐52425 Jülich, Germany 2: Technical University of Denmark, DK‐2800 Kgs. Lyngby, Denmark
Publication date: September 20, 2006