In this paper we propose a new hierarchical non stationary image prior for image restoration. This prior captures the directional edges using a continuous model and regularizes accordingly the restored images. In addition, the corresponding generative graphical model does not contain cycles, thus learning this model is easy and fast. Based on this prior image model, a maximum a posteriori (MAP) estimation algorithm is derived. Numerical experiments are provided that demonstrate the advantages of the proposed non stationary model as compared with algorithms that use stationary models.


    Zugriff

    Zugriff prüfen

    Verfügbarkeit in meiner Bibliothek prüfen

    Bestellung bei Subito €


    Exportieren, teilen und zitieren



    Titel :

    Maximum a posteriori image restoration based on a new directional continuous edge image prior


    Beteiligte:
    Chantas, G. (Autor:in) / Galatsanos, N. (Autor:in) / Likas, A. (Autor:in)


    Erscheinungsdatum :

    01.01.2005


    Format / Umfang :

    457140 byte




    Medientyp :

    Aufsatz (Konferenz)


    Format :

    Elektronische Ressource


    Sprache :

    Englisch



    Maximum a Posteriori Image Restoration Based on a New Directional Continuous Edge Image Prior

    Chantas, G. / Galatsanos, N. / Likas, A. | British Library Conference Proceedings | 2005



    Maximum a posteriori image registration/motion estimation

    Oshman, Yaakov / Menis, Baruch | AIAA | 1994


    Traffic Image Segmentation Based on Maximum Posteriori Mutual Information

    Cao, L. / Shi, Z.-k. / Chen, W. | British Library Conference Proceedings | 2009


    Traffic image segmentation based on maximum posteriori mutual information

    Cao, Li / Shi, Zhong-ke / Chen, Wen | IEEE | 2009