This paper is concerned with image denoising approaches. The detail exponents of image transformed by Wavelet have been proved its significant heavy-tails nature. The alpha stable distribution has a generality to represent heavy-tailed and impulsive nature. However, the probability density function of such a statistics model has no closed expression. Based on a tractable approximation, BCGM model, maximum a posteriori (MAP) shrinkage is proposed for removing additive. Since the prior distributions are analytically known after BCGM is introduced, MAP approach becomes now more tractable than fore methods.


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    Title :

    BCGM based MAP denoising in wavelet domain


    Contributors:
    Xutao Li, (author) / Jiajia Ren, (author) / Yunkai Feng, (author)


    Publication date :

    2010-06-01


    Size :

    1591213 byte




    Type of media :

    Conference paper


    Type of material :

    Electronic Resource


    Language :

    English



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