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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    Title :

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


    Contributors:


    Publication date :

    2005-01-01


    Size :

    398677 byte




    Type of media :

    Conference paper


    Type of material :

    Electronic Resource


    Language :

    English



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