• DocumentCode
    2154110
  • Title

    A new variational method for preserving point-like and curve-like singularities in 2-D images

  • Author

    Graziani, Daniele ; Blanc-Féraud, Laure ; Aubert, Gilles

  • Author_Institution
    ARIANA CNRS/INRIA/UNSA Sophia Antipolis, Sophia Antipolis, France
  • fYear
    2011
  • fDate
    22-27 May 2011
  • Firstpage
    937
  • Lastpage
    940
  • Abstract
    We propose a new variational method to restore point-like and curve-like singularities in 2-D images. As points and open curves are fine structures, they are difficult to restore by means of first order derivative operators computed in the noisy image. In this paper we propose to use the Laplacian operator of the observed intensity, since it be comes singular at points and curves. Then we propose to restore these singularities by introducing suitable regularization involving the M-norm of the Laplacian operator. Results are shown on synthetic an real data.
  • Keywords
    image restoration; variational techniques; 2D image restoration; Laplacian operator; curve-like singularity; first order derivative operator; l1-norm operator; noisy image; open curve; point-like singularity; variational method; Biomedical imaging; Image restoration; Laplace equations; Minimization; Noise measurement; PSNR; Nesterov scheme; image processing; l1-minimization; laplacian operator; non smooth convex optimization;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Acoustics, Speech and Signal Processing (ICASSP), 2011 IEEE International Conference on
  • Conference_Location
    Prague
  • ISSN
    1520-6149
  • Print_ISBN
    978-1-4577-0538-0
  • Electronic_ISBN
    1520-6149
  • Type

    conf

  • DOI
    10.1109/ICASSP.2011.5946559
  • Filename
    5946559