We address the problem of image deconvolution under I/sub p/ norm (and other) penalties expressed in the wavelet domain. We propose an algorithm based on the bound optimization approach; this approach allows deriving EM-type algorithms without using the concept of missing/hidden data. The algorithm has provable monotonicity both with orthogonal or redundant wavelet transforms. We also derive bounds on the l/sub p/ norm penalties to obtain closed form update equations for any p /spl isin/ [0, 2]. Experimental results show that the proposed method achieves state-of-the-art performance.


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    Title :

    A bound optimization approach to wavelet-based image deconvolution


    Contributors:


    Publication date :

    2005-01-01


    Size :

    150621 byte




    Type of media :

    Conference paper


    Type of material :

    Electronic Resource


    Language :

    English



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