• DocumentCode
    2482124
  • Title

    Edge Preserving Image Denoising in Reproducing Kernel Hilbert Spaces

  • Author

    Bouboulis, Pantelis ; Theodoridis, Sergios ; Slavakis, Konstantinos

  • Author_Institution
    Dept. of Inf. & Telecommun., Univ. of Athens, Athens, Greece
  • fYear
    2010
  • fDate
    23-26 Aug. 2010
  • Firstpage
    2660
  • Lastpage
    2663
  • Abstract
    The goal of this paper is the development of a novel approach for the problem of Noise Removal, based on the theory of Reproducing Kernels Hilbert Spaces (RKHS). The problem is cast as an optimization task in a RKHS, by taking advantage of the celebrated semi parametric Representer Theorem. Examples verify that in the presence of gaussian noise the proposed method performs relatively well compared to wavelet based techniques and outperforms them significantly in the presence of impulse or mixed noise.
  • Keywords
    Gaussian noise; Hilbert spaces; image denoising; optimisation; wavelet transforms; Gaussian noise; edge preserving image denoising; noise removal; optimization task; reproducing kernel Hilbert spaces; semi parametric representer theorem; wavelet based techniques; Hilbert space; Image denoising; Image edge detection; Kernel; Noise; Noise reduction; Pixel;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Pattern Recognition (ICPR), 2010 20th International Conference on
  • Conference_Location
    Istanbul
  • ISSN
    1051-4651
  • Print_ISBN
    978-1-4244-7542-1
  • Type

    conf

  • DOI
    10.1109/ICPR.2010.652
  • Filename
    5596011