Visualization and unsupervised classification of changes in multispectral satellite imagery

Morton J. Canty, Allan A. Nielsen

AbstractThe 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.
TypeJournal paper [With referee]
JournalInternational Journal of Remote Sensing
Year2006    Vol. 27    No. 18    pp. 3961-3975
AddressRichard Petersens Plads, Building 321
SeriesTechnical University of Denmark
ISBN / ISSNDOI:10.1080/01431160500222608
Electronic version(s)[pdf]
BibTeX data [bibtex]
IMM Group(s)Image Analysis & Computer Graphics, Geoinformatics