• DocumentCode
    2963244
  • Title

    A Method of CCD Noise Removal Using the Contourlet Transform in Digital Images

  • Author

    Tian, Yong ; Wang, Zhaodong

  • Author_Institution
    State Key Lab. of Rolling & Autom., Northeastern Univ., Shenyang, China
  • Volume
    2
  • fYear
    2011
  • fDate
    28-29 March 2011
  • Firstpage
    350
  • Lastpage
    353
  • Abstract
    In the field of image processing, it is inevitable to contain various noises in the image signals obtaining by the CCD camera. CCD noise model is a combination of a mixture of a fixed-pattern noise and multiplicative Gaussian noise and a mixture of signal-independent noise. Based on the model, this paper proposed a method to remove the noise from digital images corrupted by CCD device. The method developed a de-noising algorithm to restore images contaminated by the CCD noise sources. Because the great correlation exists among the wavelet coefficients, this paper adopts contourlet transform based on an efficient two-dimensional multiscale and directional filter bank that can deal effectively with images having smooth contours. The scheme will sharpen the edges and smooth the uniform area at the same time. At the end of the paper, it performed analysis and simulations to understand the performance of the scheme. The results indicated that the de-noising method is efficient.
  • Keywords
    Gaussian noise; filtering theory; image denoising; image restoration; wavelet transforms; CCD noise removal; contourlet transform; digital images; directional filter bank; fixed-pattern noise; image denoising; image processing; image restoration; multiplicative Gaussian noise; signal-independent noise; two-dimensional multiscale filter bank; wavelet coefficients; Charge coupled devices; Noise; Noise measurement; Noise reduction; Spinning; Wavelet transforms;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Intelligent Computation Technology and Automation (ICICTA), 2011 International Conference on
  • Conference_Location
    Shenzhen, Guangdong
  • Print_ISBN
    978-1-61284-289-9
  • Type

    conf

  • DOI
    10.1109/ICICTA.2011.371
  • Filename
    5750896