• DocumentCode
    236904
  • Title

    A new fractional-order variational model for speckled de-noising

  • Author

    Hacini, Meriem ; Hachouf, Fella ; Djemal, Khalifa

  • Author_Institution
    Lab. d´ Autom. et de Robot., Univ. Constantine, Constantine, Algeria
  • fYear
    2014
  • fDate
    10-12 Dec. 2014
  • Firstpage
    1
  • Lastpage
    6
  • Abstract
    In this paper, a novel speckled image de-noising algorithm is proposed. A fractional-order multiplicative variational model is included as a multiplicative constraint in the regularization problem thereby the appropriate regularization parameter will be controlled by the optimization process itself. An adaptive selection method based on image regions property is used for the selection of the appropriate fractional-order value. The proposed algorithm not only overcomes the disadvantage of generating artificial edges but also has the advantage of de-noising and edges preservation.Experimental results show that the fractional order multiplicative variational model can improve the Peak Signal to Noise Ratio (PSNR) of image, preserve image structures and overcomes the disadvantage of generating artificial edges in the de-noising process.
  • Keywords
    image denoising; optimisation; speckle; variational techniques; PSNR; adaptive selection method; artificial edge generation; edge preservation; fractional-order multiplicative variational model; optimization process; peak signal to noise ratio; speckled image denoising algorithm; Image denoising; Image edge detection; Mathematical model; Noise reduction; PSNR; Speckle; Fractional- order; Image De-noising; Multiplicative Variational model;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Visual Information Processing (EUVIP), 2014 5th European Workshop on
  • Conference_Location
    Paris
  • Type

    conf

  • DOI
    10.1109/EUVIP.2014.7018384
  • Filename
    7018384