We propose a new solution to the problem of obtaining a single high-resolution image from multiple blurred, noisy, and undersampled images. Our estimator, derived using the Bayesian stochastic framework, is novel in that it employs a new hierarchical non-stationary image prior. This prior adapts the restoration of the super-resolved image to the local spatial statistics of the image. Numerical experiments demonstrate the effectiveness of the proposed approach.


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    Titel :

    Non-stationary approximate Bayesian super-resolution using a hierarchical prior model


    Beteiligte:
    Woods, N.A. (Autor:in) / Galatsanos, N.P. (Autor:in)


    Erscheinungsdatum :

    01.01.2005


    Format / Umfang :

    398677 byte




    Medientyp :

    Aufsatz (Konferenz)


    Format :

    Elektronische Ressource


    Sprache :

    Englisch



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