• DocumentCode
    3398517
  • Title

    Wavelet image denoising algorithm based on local adaptive wiener filtering

  • Author

    Li Dan ; Wang Yan ; Fang Ting

  • Author_Institution
    Sch. of Electr. Eng. & Inf., Anhui Univ. of Technol., Maanshan, China
  • fYear
    2011
  • fDate
    19-22 Aug. 2011
  • Firstpage
    2305
  • Lastpage
    2307
  • Abstract
    There are many interference noise in industrial site, it affect the image quality of industry seriously. In view of these question, this paper demonstrate a wavelet image denoising algorithm based on local Wiener filtering with directional windows to replace the traditional denoising methods. Consider the direction of each wavelet sub-band, this algorithm use different shapes of the neighborhood window in different sub-band to estimated the variance of wavelet coefficients, the algorithm is applied to the detection of the blast furnace´s looking-fire-hole image. Experimental results show that the proposed method obtain good results in both the Gaussian image denoising and keep the details of image.
  • Keywords
    Gaussian processes; Wiener filters; blast furnaces; image denoising; metallurgy; production engineering computing; wavelet transforms; Gaussian image denoising; blast furnace looking-fire-hole image detection; directional windows; image details; image quality; industrial site; interference noise; local adaptive Wiener filtering; wavelet coefficients; wavelet image denoising algorithm; wavelet subband; Image denoising; Wavelet coefficients; Wavelet domain; Wiener filter; Wiener filtering; adaptive window; image denoising; wavelet transform;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Mechatronic Science, Electric Engineering and Computer (MEC), 2011 International Conference on
  • Conference_Location
    Jilin
  • Print_ISBN
    978-1-61284-719-1
  • Type

    conf

  • DOI
    10.1109/MEC.2011.6025954
  • Filename
    6025954