The problem of reinforcing local evidence of edges while suppressing unwanted information in noisy images is considered using a form of relaxation labeling. The methodology is based on parameterizing a continuous set of edge orientation labels using a single vector. A sigmoidal thresholding function similar to that used in artificial neural networks to bias neighborhood-influence and insure convergence to meaningful stable states is also utilized. A global optimization function is defined, and a decentralized parallel algorithm is derived that uses a steepest-gradient-descent approach to arrive at the optimal point on the functional surface, corresponding to desirable edge-reinforced and noise-suppressed labelings. In addition, a modification to the functional is presented which incorporates a thinning operation to insure that each edge is marked by only a single-pixel-wide response. Results from several image data sets indicate that the algorithm performs as well as or better than other relaxation labeling methods, and with improved computational efficiency.<>


    Zugriff

    Zugriff prüfen

    Verfügbarkeit in meiner Bibliothek prüfen

    Bestellung bei Subito €


    Exportieren, teilen und zitieren



    Titel :

    Edge reinforcement using parametrized relaxation labeling


    Beteiligte:
    Duncan, J.S. (Autor:in) / Birkholzer, T. (Autor:in)


    Erscheinungsdatum :

    01.01.1989


    Format / Umfang :

    927757 byte





    Medientyp :

    Aufsatz (Konferenz)


    Format :

    Elektronische Ressource


    Sprache :

    Englisch




    Parametrized Supersonic Transport Configurations

    Sobieczky, H. / Radespiel, R. / Confederation of European Aerospace Societies | British Library Conference Proceedings | 1995


    Parametrized Motion Planning and Topological Complexity

    Farber, Michael / Weinberger, Shmuel | Springer Verlag | 2022


    Pixel labeling by supervised probabilistic relaxation

    Landgrebe, D. A. / Richards, J. A. / Swain, P. H. | NTRS | 1980


    Multiscale relaxation labeling of fractal images

    Choate, J.A. / Gennert, M.A. | IEEE | 1993