• DocumentCode
    3210004
  • Title

    An improved PCNN model and a new removing algorithm of salt and pepper noise

  • Author

    Wu, Yan ; Xu, Bing ; Bian, Xiao-Yue

  • Author_Institution
    Dept. of Comput. Sci. & Technol., Tongji Univ., Shanghai, China
  • Volume
    2
  • fYear
    2010
  • fDate
    13-14 Sept. 2010
  • Firstpage
    178
  • Lastpage
    182
  • Abstract
    An improved PCNN model-PCNN with Positive and Negative Firing, PCNNPNF-is proposed, and also put forward a de-noising algorithm based on the time matrix of PCNNPNF. The biggest improvement is that the neuron´s output of improved PCNN has three states: positive firing, negative firing and no firing, while PCNN only has two states: firing and no firing. Experimental results show that the de-noising algorithm based on PCNNPNF can quickly find the two kinds of pulse noises, remove these noises, and reserve more information than PCNN.
  • Keywords
    image denoising; matrix algebra; neural nets; PCNN model; PCNNPNF; denoising algorithm; negative firing; positive firing; removing algorithm; salt and pepper noise; time matrix; Computational modeling; Image segmentation; Neurons; Noise; Speech; PCNN with positive and negative firing; de-noising algorithm; pulse noise;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Computational Intelligence and Natural Computing Proceedings (CINC), 2010 Second International Conference on
  • Conference_Location
    Wuhan
  • Print_ISBN
    978-1-4244-7705-0
  • Type

    conf

  • DOI
    10.1109/CINC.2010.5643758
  • Filename
    5643758