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.<>


    Zugriff

    Zugriff prüfen

    Verfügbarkeit in meiner Bibliothek prüfen

    Bestellung bei Subito €


    Exportieren, teilen und zitieren



    Titel :

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


    Beteiligte:
    Comer, M.L. (Autor:in) / Delp, E.J. (Autor:in)


    Erscheinungsdatum :

    01.01.1994


    Format / Umfang :

    430528 byte




    Medientyp :

    Aufsatz (Konferenz)


    Format :

    Elektronische Ressource


    Sprache :

    Englisch



    Parameter Estimation and Segmentation of Noisy or Textured Images using the EM Algorithm and MPM Estimation

    Comer, M. L. / Delp, E. J. / IEEE; Signal Processing Society | British Library Conference Proceedings | 1994


    Segmentation of textured images

    Perry, A. / Lowe, D.G. | IEEE | 1989



    High-Scale Edge Study for Segmentation and Contour Closing in Textured or Noisy Images

    Huet, F. / Philipp, S. / University of Arizona et al. | British Library Conference Proceedings | 1998


    Unsupervised segmentation based on Von Mises circular distributions for orientation estimation in textured images

    Da Costa, J.-P. / Galland, F. / Roueff, A. et al. | British Library Online Contents | 2012