• DocumentCode
    2085152
  • Title

    Image Denoise Using Auto-Adapted Empirical Mode Decomposition Algorithm

  • Author

    Liang, LingFei ; Ping, Ziliang

  • Author_Institution
    Sch. of Electron. Eng., Beijing Univ. of Posts & Telecommun., Beijing, China
  • fYear
    2009
  • fDate
    17-19 Oct. 2009
  • Firstpage
    1
  • Lastpage
    4
  • Abstract
    In this paper, a new image denoise method is presented. The main contribution of our approach is to apply an auto-adapted empirical mode decomposition algorithm (AAEMD) to remove the noise. By means of AAEMD, the image can be decomposed into a number of intrinsic mode function (IMF), and the histogram of IMF observes the normal distribution, whether the original image has noise or not. Here, histogram matching is applied for denoise in the first few IMF images. In other words, the histogram of the new IMF images after Appling histogram matching observes the special normal distribution. At last, the modified and unmodified IMF images are added up to get the denoise image. Experiments prove that the novel algorithm is efficient in image denosise and better than current algorithms.
  • Keywords
    image denoising; image matching; auto-adapted empirical mode decomposition; histogram matching; image denoising; intrinsic mode function; Acoustic reflection; Data analysis; Frequency; Gaussian distribution; Histograms; Image analysis; Physics; Signal analysis; Signal processing; Wavelet analysis;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Image and Signal Processing, 2009. CISP '09. 2nd International Congress on
  • Conference_Location
    Tianjin
  • Print_ISBN
    978-1-4244-4129-7
  • Electronic_ISBN
    978-1-4244-4131-0
  • Type

    conf

  • DOI
    10.1109/CISP.2009.5301486
  • Filename
    5301486