• DocumentCode
    2648960
  • Title

    Wavelet image de-noising method based on noise standard deviation estimation

  • Author

    Zhao, Zhen-bing ; Yuan, Jin-sha ; Gao, Qiang ; Kong, Ying-hui

  • Author_Institution
    North China Electr. Power Univ., Baoding
  • Volume
    4
  • fYear
    2007
  • fDate
    2-4 Nov. 2007
  • Firstpage
    1910
  • Lastpage
    1914
  • Abstract
    Wavelet threshold de-noising method is an important approach for image de-noising. In the paper, the standard deviation estimation of image noise was introduced, and its correction was given. Based on its correction, a wavelet shrinkage threshold method of image de-noising was proposed. The principle of wavelet image de-noising was discussed. The standard deviation of image noise was estimated by the difference between two Laplace templates. According to the different behaviors of the useful signal and the noise in wavelet domain, image de-noising method was designed. It can be seen from the de-noising results of simulation images and temperature field images that the proposed method can estimate the noise standard deviation well, improve the peak signal-to-noise ratio and the visual quality, and remove the noise from the image effectively. And it shows the method is better than other traditional ones, too.
  • Keywords
    Laplace transforms; image denoising; wavelet transforms; Laplace templates; noise standard deviation estimation; signal-to-noise ratio; wavelet image denoising method; wavelet threshold denoising method; Image analysis; Image denoising; Image reconstruction; Noise reduction; Notice of Violation; PSNR; Pattern analysis; Pattern recognition; Wavelet analysis; Wavelet domain; Noise standard deviation; image de-noising; threshold process; wavelet transform;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Wavelet Analysis and Pattern Recognition, 2007. ICWAPR '07. International Conference on
  • Conference_Location
    Beijing
  • Print_ISBN
    978-1-4244-1065-1
  • Electronic_ISBN
    978-1-4244-1066-8
  • Type

    conf

  • DOI
    10.1109/ICWAPR.2007.4421768
  • Filename
    4421768