Presents a new algorithm for segmentation of noisy or textured images using the expectation-maximization (EM) algorithm for estimating parameters of the probability mass function of the pixel class labels and the maximization of the posterior marginals (MPM) criterion for the segmentation operation. A Markov random field (MRF) model is used for the pixel class labels. The authors present experimental results demonstrating the use of the new algorithm on synthetic images and medical imagery.<>


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    Title :

    Parameter estimation and segmentation of noisy or textured images using the EM algorithm and MPM estimation


    Contributors:
    Comer, M.L. (author) / Delp, E.J. (author)


    Publication date :

    1994-01-01


    Size :

    430528 byte




    Type of media :

    Conference paper


    Type of material :

    Electronic Resource


    Language :

    English



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