A natural scene statistics (NSS) based blind image denoising approach is proposed, where denoising is performed without knowledge of the noise variance present in the image. We show how such a parameter estimation can be used to perform blind denoising by combining blind parameter estimation with a state-of-the-art denoising algorithm.1 Our experiments show that for all noise variances simulated on a varied image content, our approach is almost always statistically superior to the reference BM3D implementation in terms of perceived visual quality at the 95% confidence level.


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    Titel :

    Automatic parameter prediction for image denoising algorithms using perceptual quality features


    Beteiligte:
    Mittal, Anish (Autor:in) / Moorthy, Anush K. (Autor:in) / Bovik, Alan C. (Autor:in)

    Kongress:

    Human Vision and Electronic Imaging XVII ; 2012 ; Burlingame,California,USA


    Erschienen in:

    Erscheinungsdatum :

    2012-02-05





    Medientyp :

    Aufsatz (Konferenz)


    Format :

    Elektronische Ressource


    Sprache :

    Englisch



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