• DocumentCode
    596644
  • Title

    A new wavelet hard threshold to process image with strong Gaussian Noise

  • Author

    Cheng Chen ; Ningning Zhou

  • Author_Institution
    Comput. Coll., Nanjing Univ. of posts & Telecommun., Nanjing, China
  • fYear
    2012
  • fDate
    18-20 Oct. 2012
  • Firstpage
    558
  • Lastpage
    561
  • Abstract
    Wavelet transform method has been widely used in image filtering, the wavelet threshold de-noising method can treat Gaussian noise with randomness well. This paper proposes that after the wavelet transform the high frequency coefficients need a more accurate processing, And the classical hard threshold method has been improved by introducing the measure of medium truth scale. The new method can effectively handle strong Gaussian noise with larger variance through theoretical analysis and experimental simulation, and get a fine recovery image. It also provides a new approach for wavelet de-noising.
  • Keywords
    Gaussian noise; filtering theory; image denoising; image restoration; image segmentation; wavelet transforms; fine image recovery; high frequency coefficients; image filtering; image processing; medium truth scale; strong Gaussian noise handling; wavelet hard threshold; wavelet threshold denoising method; wavelet transform method; Filtering; Gaussian noise; Noise reduction; Pollution measurement; Wavelet transforms;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Advanced Computational Intelligence (ICACI), 2012 IEEE Fifth International Conference on
  • Conference_Location
    Nanjing
  • Print_ISBN
    978-1-4673-1743-6
  • Type

    conf

  • DOI
    10.1109/ICACI.2012.6463226
  • Filename
    6463226