The natural characteristics of image signals and the statistics of measurement noise are decisive for designing optimal filter sets and optimal estimation methods in signal processing. Astonishingly, this principle has so far only partially found its way into the field of image sequence processing. We show how a Wiener-type MMSE optimization criterion for the resulting image signal, based on a simple covariance model of images or image sequences, provides direct and intelligible solutions for various, apparently different, problems, such as error concealment, or adaption of filters to signal and noise statistics.


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    Title :

    A statistical unification of image interpolation, error concealment, and source-adapted filter design


    Contributors:
    Muhlich, M. (author) / Mester, R. (author)


    Publication date :

    2004-01-01


    Size :

    367858 byte




    Type of media :

    Conference paper


    Type of material :

    Electronic Resource


    Language :

    English



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