• DocumentCode
    3640869
  • Title

    A bivariate shrinkage function for wavelet-based denoising

  • Author

    Levent Şendur;Ivan W. Selesnick

  • Author_Institution
    Electrical Engineering, Polytechnic University, 6 Metrotech Center, Brooklyn, NY 11201, USA
  • Volume
    2
  • fYear
    2002
  • fDate
    5/1/2002 12:00:00 AM
  • Abstract
    Most simple nonlinear thresholding rules for wavelet-based denoising assume the wavelet coefficients are independent. However, wavelet coefficients of natural images have significant dependency. In this paper, a new heavy-tailed bivariate pdf is proposed to model the statistics of wavelet coefficients, and a simple nonlinear threshold function (shrinkage function) is derived from the pdf using Bayesian estimation theory. The new shrinkage function does not assume the independence of wavelet coefficients.
  • Keywords
    "Argon","Computational modeling","Noise measurement"
  • Publisher
    ieee
  • Conference_Titel
    Acoustics, Speech, and Signal Processing (ICASSP), 2002 IEEE International Conference on
  • ISSN
    1520-6149
  • Print_ISBN
    0-7803-7402-9
  • Type

    conf

  • DOI
    10.1109/ICASSP.2002.5744031
  • Filename
    5744031