Method of unsupervised segmentation of polarimetric synthetic-aperture-radar (SAR) image data into classes involves selection of classes on basis of multidimensional fuzzy clustering of logarithms of parameters of polarimetric covariance matrix. Data in each class represent parts of image wherein polarimetric SAR backscattering characteristics of terrain regarded as homogeneous. Desirable to have each class represent type of terrain, sea ice, or ocean surface distinguishable from other types via backscattering characteristics. Unsupervised classification does not require training areas, is nearly automated computerized process, and provides nonsubjective selection of image classes naturally well separated by radar.


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    Titel :

    Unsupervised Segmentation Of Polarimetric SAR Data


    Beteiligte:
    Rignot, Eric J. (Autor:in) / Dubois, Pascale (Autor:in) / Van Zyl, Jakob (Autor:in) / Kwok, Ronald (Autor:in) / Chellappa, Rama (Autor:in)

    Erschienen in:

    Erscheinungsdatum :

    1994-07-01



    Medientyp :

    Sonstige


    Format :

    Keine Angabe


    Sprache :

    Englisch


    Schlagwörter :



    Segmentation Of Polarimetric SAR Data

    Rignot, Eric J. M. / Chellappa, Rama | NTRS | 1994



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