Markov random field models in image remote sensing

Jean-Paul Rasson, Vincent Granville

    Research output: Contribution in Book/Catalog/Report/Conference proceedingConference contribution

    Abstract

    During the last few years, Markov Random Field (Mrf) models have already been successfully applied in some applications in image remote sensing in a context of conditional maximum likelihood estimation. Here, in the same context, we propose some original uses of Mrf, especially in image segmentation, noise filtering and discriminant analysis. For instance, we propose a Mrf model on the spectral signatures space, a strongly unified approach to classification and noise filtering as well as a particular model of noise.
    Original languageEnglish
    Title of host publicationComputer Intensive Methods in Statistics
    PublisherPhysica Heidelberg
    Pages98-112
    Number of pages15
    ISBN (Electronic)978-3-642-52468-4
    ISBN (Print)978-3-7908-0677-9
    Publication statusPublished - 1993

    Publication series

    NameStatistic and Computing
    PublisherPhysica Heidelberg
    ISSN (Print)1431-8784
    ISSN (Electronic)2197-1706

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