Unsupervised classification of changes in multispectral satellite imagery

Morton J. Canty, Allan Aasbjerg Nielsen, Lorenzo Bruzzone (Editor)

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    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.
    Original languageEnglish
    Title of host publicationProceedings of SPIE, Image and Signal Processing for Remote Sensing X
    Publication date2004
    Pages356-363
    Publication statusPublished - 2004

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