• DocumentCode
    2151953
  • Title

    Applying an improved neural network to impulse noise removal

  • Author

    Deng, Chao ; Liu, Hong-Min ; Wang, Zhi-Heng

  • Author_Institution
    Coll. of Comput. Sci. & Technol., Henan Polytech. Univ., Jiaozuo, China
  • fYear
    2010
  • fDate
    11-14 July 2010
  • Firstpage
    207
  • Lastpage
    210
  • Abstract
    A new noise removal algorithm based on improved neural network, is applied to remove the impulse noise of the digital images. First of all, an improved neural network is used to detect the noise-pixels and distinguish it from noise-free pixels efficiently; Second, the noise-pixels are replaced further by the suitable pixel which has the most local similarity; Finally, the output is the combination of the noise-free pixels and the suitable pixel. The proposed algorithm is capable of removing the impulse noise effectively. At the same time it can keep more image details well. Experiential results show that the new algorithm is more improved than the conventional filters.
  • Keywords
    image denoising; image enhancement; neural nets; digital images; impulse noise removal; neural network; noise free image pixels; noise pixels detection; Algorithm design and analysis; Artificial neural networks; Filtering algorithms; Image restoration; Noise; Optical filters; Pixel; Image enhancement; Image processing; Impulse noise; Local similarity analysis; Neural network;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Wavelet Analysis and Pattern Recognition (ICWAPR), 2010 International Conference on
  • Conference_Location
    Qingdao
  • Print_ISBN
    978-1-4244-6530-9
  • Type

    conf

  • DOI
    10.1109/ICWAPR.2010.5576334
  • Filename
    5576334