• DocumentCode
    2458850
  • Title

    Sparsity based Poisson denoising

  • Author

    Giryes, Raja ; Elad, Michael

  • Author_Institution
    Dept. of Comput. Sci., Technion - Israel Inst. of Technol., Haifa, Israel
  • fYear
    2012
  • fDate
    14-17 Nov. 2012
  • Firstpage
    1
  • Lastpage
    5
  • Abstract
    Sparsity based techniques have been widely used for image denoising. In this work we focus on Poisson noise and propose initial stages for a new strategy for its removal. We start with a method that removes the noise by converting it into an additive Gaussian noise using the Anscombe transform, applying a variant of the OMP-denoising algorithm. Then, following the recent work by Salmon et. al., we bypass the need for the Anscombe transform and rely directly on the noise statistics. The new strategy is shown to lead to near state-of-the-art results.
  • Keywords
    Gaussian noise; image denoising; Anscombe transform; Gaussian noise; OMP-denoising algorithm; Salmon et al; image denoising; noise statistics; sparsity based poisson denoising; Approximation algorithms; Dictionaries; Noise measurement; Noise reduction; PSNR; Transforms;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Electrical & Electronics Engineers in Israel (IEEEI), 2012 IEEE 27th Convention of
  • Conference_Location
    Eilat
  • Print_ISBN
    978-1-4673-4682-5
  • Type

    conf

  • DOI
    10.1109/EEEI.2012.6377139
  • Filename
    6377139