In improved scheme for Bayesian classification of picture elements in polarimetric synthetic-aperture radar image of terrain, priori probability that given picture element belongs to given class, adjusted according to spatial variation of statistical properties of image data. Accuracy increases dramatically in first few iterations. Scheme involves sequence of classifications. In first, a priori probability that element belongs to class taken to be constant over the whole image. In subsequent classifications, adaptive a priori probabilities calculated for each picture element.


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    Title :

    Iterative Bayesian Classification In Polarimetric SAR


    Contributors:

    Published in:

    Publication date :

    1992-09-01



    Type of media :

    Miscellaneous


    Type of material :

    No indication


    Language :

    English






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