• DocumentCode
    2463169
  • Title

    An Adaptive Filtering Method for Mixed Noise of Images

  • Author

    Su Te-Jen ; Li Chuan-I

  • Author_Institution
    Electron. Eng., Nat. Kaohsiung Univ. of Appl. Sci., Kaohsiung, Taiwan
  • fYear
    2012
  • fDate
    4-6 June 2012
  • Firstpage
    698
  • Lastpage
    701
  • Abstract
    Images are often affected by different noise interference in the transmission process. The noise cause wrong information in image analysis. To reduce noise, the simple and easy method is that receiving a few images once time and averages those images to get an average image. But, this method casts huge time cost. If it is difficult to obtain the image, the method is more infeasible. The median filter has better performance for impulse noise and the average filter has good results for lower Gaussian noise. This paper presents a method based on median filter to filter extreme value and designs an adaptive mask according to the number of extreme value in the mask. Then, calculating the similarity for each pixel in the mask and giving weights to pixels in the mask by the principle of proportionality. To do so, the present method can achieve the goal which is removing high-intensity impulse noise and reducing mixed noised interference.
  • Keywords
    Gaussian noise; adaptive filters; image denoising; image matching; impulse noise; Gaussian noise; adaptive filtering method; adaptive mask; average filter; extreme value filter; high-intensity impulse noise; image analysis; images mixed noise; mask pixels; median filter; mixed noised interference reduction; noise reduction; pixel similarity; proportionality principle; transmission process; Adaptive filters; Gaussian noise; Image edge detection; Information filters; PSNR; high-intensity impulse noise; median filter; mixed noised; similarity;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Computer, Consumer and Control (IS3C), 2012 International Symposium on
  • Conference_Location
    Taichung
  • Print_ISBN
    978-1-4673-0767-3
  • Type

    conf

  • DOI
    10.1109/IS3C.2012.181
  • Filename
    6228404