• DocumentCode
    1434691
  • Title

    Adaptive denoising based on SURE risk

  • Author

    Zhang, Xiao-Ping ; Desai, Mita D.

  • Author_Institution
    Div. of Eng., Texas Univ., San Antonio, TX, USA
  • Volume
    5
  • Issue
    10
  • fYear
    1998
  • Firstpage
    265
  • Lastpage
    267
  • Abstract
    A new adaptive denoising method is presented based on Stein´s (1981) unbiased risk estimate (SURE) and on a new class of thresholding functions. First, we present a new class of thresholding functions that has a continuous derivative while the derivative of standard soft-thresholding function is not continuous. The new thresholding functions make it possible to construct the adaptive algorithm whenever using the wavelet shrinkage method. By using the new thresholding functions, a new adaptive denoising method is presented based on SURE. Several numerical examples are given. The results indicated that for denoising applications, the proposed method is very effective in adaptively finding the optimal solution in a mean square error (MSE) sense. It is also shown that this method gives better MSE performance than those conventional wavelet shrinkage methods.
  • Keywords
    adaptive signal processing; functional analysis; least mean squares methods; noise; wavelet transforms; MSE performance; SURE risk; Stein´s unbiased risk estimate; adaptive algorithm; adaptive denoising method; continuous derivative; mean square error; optimal solution; soft-thresholding function; thresholding functions; wavelet shrinkage method; Adaptive algorithm; Discrete wavelet transforms; Gaussian noise; Mean square error methods; Minimax techniques; Noise reduction; Optimization methods; Wavelet coefficients; Wavelet domain; White noise;
  • fLanguage
    English
  • Journal_Title
    Signal Processing Letters, IEEE
  • Publisher
    ieee
  • ISSN
    1070-9908
  • Type

    jour

  • DOI
    10.1109/97.720560
  • Filename
    720560