Many sensing techniques and image processing applications are characterized by noisy, or corrupted, image data. Anisotropic diffusion is a popular, and theoretically well understood, technique for denoising such images. Diffusion approaches however require the selection of an "edge stopping" function, the definition of which is typically ad hoc. We exploit and extend recent work on the statistics of natural images to define principled edge stopping functions for different types of imagery. We consider a variety of anisotropic diffusion schemes and note that they compute spatial derivatives at fixed scales from which we estimate the appropriate algorithm-specific image statistics. Going beyond traditional work on image statistics, we also model the statistics of the eigenvalues of the local structure tensor. Novel edge-stopping functions are derived from these image statistics giving a principled way of formulating anisotropic diffusion problems in which all edge-stopping parameters are learned from training data.


    Access

    Check access

    Check availability in my library

    Order at Subito €


    Export, share and cite



    Title :

    Image statistics and anisotropic diffusion


    Contributors:
    Scharr, (author) / Black, (author) / Haussecker, (author)


    Publication date :

    2003-01-01


    Size :

    1123564 byte




    Type of media :

    Conference paper


    Type of material :

    Electronic Resource


    Language :

    English



    Image Statistics and Anisotropic Diffusion

    Scharr, H. / Black, M. / Haussecker, H. et al. | British Library Conference Proceedings | 2003


    Image Compression with Anisotropic Diffusion

    Galić, I. | British Library Online Contents | 2008


    Anisotropic Diffusion Pyramids for Image Segmentation

    Acton, S. T. / Bovik, A. C. / Crawford, M. M. et al. | British Library Conference Proceedings | 1994


    Anisotropic nonlinear diffusion approach to image sharpening

    Xie Meihua, / Wang Zhengming, | IEEE | 2005


    Anisotropic Nonlinear Diffusion approach to Image Sharpening

    Meihua, X. / Zhengming, W. | British Library Conference Proceedings | 2005