Two algorithms processing polarimetric synthetic-aperture-radar data found effective in assigning various parts of SAR images to classes representing different types of terrain. Partially automate interpretation of SAR imagery, reducing amount of photointerpretation needed and putting whole interpretation process on more quantitative and systematic basis. First algorithm implements Bayesian classification scheme "supervised" by use of training data. Second algorithm implements classification procedure unsupervised.


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    Titel :

    Classification Of Terrain In Polarimetric SAR Images


    Beteiligte:
    Van Zyl, Jakob J. (Autor:in) / Kong, Jin A. (Autor:in) / Shin, Robert T. (Autor:in) / Lim, Harold (Autor:in) / Swartz, Albert (Autor:in) / Yueh, Simon H. (Autor:in)

    Erschienen in:

    Erscheinungsdatum :

    01.03.1993



    Medientyp :

    Sonstige


    Format :

    Keine Angabe


    Sprache :

    Englisch


    Schlagwörter :


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    Polarimetric Decomposition Applied to 3D SAR Images of Forested Terrain

    Sauer, Stefan / Kugler, Florian / Lee, Seung-Kuk et al. | Deutsches Zentrum für Luft- und Raumfahrt (DLR) | 2010

    Freier Zugriff

    Statistical blind classification of terrain surfaces in SAR images

    Mata-Moya, D. / de Nicolas-Presa, J. M. / Jarabo-Amores, P. et al. | IEEE | 2011


    Passive polarimetric IR target classification

    Sadjadi, F.A. / Chun, C.S.L. | IEEE | 2001