In this paper, a new approach to the problem of impulsive noise reduction in image is presented. First, an image neighborhood hypergraph representation using a similarity measure is computed. Next, a detection procedure based on hypergraph properties is used to classify hyperedges either as noisy, or clean data. Then we apply a nonlinear filter to noisy detected pixels. The results show that the proposed method outperforms most of the basic algorithms for the reduction of impulsive noise.


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    Titel :

    Similarity hypergraph representation for impulsive noise reduction


    Beteiligte:
    Rital, S. (Autor:in) / Cherifi, H. (Autor:in)


    Erscheinungsdatum :

    01.01.2003


    Format / Umfang :

    307500 byte




    Medientyp :

    Aufsatz (Konferenz)


    Format :

    Elektronische Ressource


    Sprache :

    Englisch



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