• DocumentCode
    3495800
  • Title

    NL-Means and aggregation procedures

  • Author

    Salmon, J. ; Le Pennec, E.

  • Author_Institution
    Lab. de Probabilite et Modeles Aleatoires, Univ. Paris 7- Diderot, Chevaleret, France
  • fYear
    2009
  • fDate
    7-10 Nov. 2009
  • Firstpage
    2977
  • Lastpage
    2980
  • Abstract
    Patch based denoising methods, such as the NL-Means, have emerged recently as simple and efficient denoising methods. This paper provides a new insight on those methods by showing their connection with recent statistical aggregation techniques. Within this aggregation framework, we propose some novel patch based denoising methods. We provide some theoretical justification and then explain how to implement them with a Monte Carlo based algorithm.
  • Keywords
    Monte Carlo methods; image denoising; statistical analysis; Monte Carlo based algorithm; NL-means procedures; aggregation procedures; patch based denoising; statistical aggregation techniques; Additive noise; Diffusion processes; Gaussian noise; Image processing; Kernel; Monte Carlo methods; Noise reduction; Pixel; Smoothing methods; Statistics; Diffusion processes; Gaussian noise; Image processing; Monte Carlo methods; Statistics;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Image Processing (ICIP), 2009 16th IEEE International Conference on
  • Conference_Location
    Cairo
  • ISSN
    1522-4880
  • Print_ISBN
    978-1-4244-5653-6
  • Electronic_ISBN
    1522-4880
  • Type

    conf

  • DOI
    10.1109/ICIP.2009.5414512
  • Filename
    5414512