• DocumentCode
    2390036
  • Title

    A biologically inspired neural network for image enhancement

  • Author

    Li, Yinghua ; Pu, Tian ; Cheng, Jian

  • Author_Institution
    Sch. of Electron. Eng., Univ. of Electron. Sci. & Technol. of China, Chengdu, China
  • fYear
    2010
  • fDate
    6-8 Dec. 2010
  • Firstpage
    1
  • Lastpage
    4
  • Abstract
    A promising trend of image processing is to incorporate some knowledge on human visual system. In this paper, we propose an improved pulse coupled neural network (PCNN) for image enhancement. We apply the passive membrane equation, which is known as a model for describing the ON-OFF opponent property of the receptive fields of the retinal ganglion cells, as the linking field to modulate feeding field input of the PCNN and obtain the enhanced neural pulse as the output image. Initially, the RGB image is converted to luminance and chrominance images. Only the achromatic image is enhanced. Finally the RGB image is reconstructed from the enhanced luminance component along with the original chrominance component. The experimental results show the effectiveness of the method.
  • Keywords
    image colour analysis; image enhancement; neural nets; PCNN; biologically inspired neural network; chrominance images; human visual system; image enhancement; image processing; luminance images; pulse coupled neural network; Artificial neural networks; Educational institutions; Humans; Image enhancement; Joining processes; OFDM; Visualization; image enhancement; opponent neural network; pulse coupled neural network;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Intelligent Signal Processing and Communication Systems (ISPACS), 2010 International Symposium on
  • Conference_Location
    Chengdu
  • Print_ISBN
    978-1-4244-7369-4
  • Type

    conf

  • DOI
    10.1109/ISPACS.2010.5704686
  • Filename
    5704686