• DocumentCode
    1844368
  • Title

    Study of Information Extraction Algorithm of Poisson Noise Images Based on Fractional Order Differentiation

  • Author

    Hou Mingliang ; Liu Yuran

  • Author_Institution
    Sch. of Comput. Eng., Huaihai Inst. of Technol., Lianyungang, China
  • fYear
    2013
  • fDate
    21-23 June 2013
  • Firstpage
    766
  • Lastpage
    769
  • Abstract
    According to the characteristic of fractional order differentiation on signal processing, an information extraction algorithm based on fractional-order differentiation was presented. In the first place, by this means information extraction was carried out for Poisson noise images, and then a comprehensive analysis and comparison was carried on with the other results of information extraction using the classical integral order operator. Experimental results shows that the new method can not only extract texture information of smooth area, but also extract high-frequency edge information, and to a great extent, enjoys a better anti-noise performance for the Poisson noise.
  • Keywords
    differentiation; edge detection; feature extraction; image denoising; image texture; Poisson noise images; anti-noise performance; comprehensive analysis; fractional-order differentiation; high-frequency edge information; information extraction algorithm; integral order operator; signal processing; texture information; Poisson noise; fractional order differentiation; image information extraction; noise immunity; texture information;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Computational and Information Sciences (ICCIS), 2013 Fifth International Conference on
  • Conference_Location
    Shiyang
  • Type

    conf

  • DOI
    10.1109/ICCIS.2013.206
  • Filename
    6643122