• DocumentCode
    2113851
  • Title

    A New Kind of Hybrid Filter Based on the ICM and the Improved Peak-and-Valley Filter

  • Author

    Zhang Xiang-guang, Zhang

  • Author_Institution
    Inst. of Inf., Qingdao Univ. of Sci. & Technol., Qingdao
  • fYear
    2008
  • fDate
    18-18 Dec. 2008
  • Firstpage
    187
  • Lastpage
    190
  • Abstract
    Intersecting cortical model (ICM) has gained widely research as a new artificial neural network. It derives directly from the studies of the small mammal´s visual cortex. The improved peak-and-valley filter can keep the details of image sufficiently if the density of noise is low enough. But the image that is badly contaminated with noise, the effect of the improved peak-and-valley filter is inadequate. To overcome this shortage, this paper suggests a kind of designing project of the hybrid filter that applies the ideas of the ICM and the improved peak-and-valley filter. The theory analysis and the simulation experiments of the image processing indicate that this kind of filter can not only remove noise effectively but also keep the details of the image sufficiently.
  • Keywords
    image denoising; median filters; neural nets; ICM; artificial neural network; hybrid filter; image noise removal; intersecting cortical model; median filter; nonlinear filter; peak-and-valley filter; Adaptive filters; Algorithm design and analysis; Analytical models; Brain modeling; Image analysis; Image processing; Information filtering; Information filters; Neural networks; Nonlinear filters; Peak-and-Valley filter; high-frequency detail; intersecting cortical model; median filter; nonlinear filter;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Future BioMedical Information Engineering, 2008. FBIE '08. International Seminar on
  • Conference_Location
    Wuhan, Hubei
  • Print_ISBN
    978-0-7695-3561-6
  • Type

    conf

  • DOI
    10.1109/FBIE.2008.45
  • Filename
    5076715