• DocumentCode
    1304877
  • Title

    Adaptive Noise Variance Estimation in BayesShrink

  • Author

    Hashemi, Masoud ; Beheshti, Soosan

  • Author_Institution
    Dept. of Electr. & Comput. Eng., Ryerson Univ., Toronto, ON, Canada
  • Volume
    17
  • Issue
    1
  • fYear
    2010
  • Firstpage
    12
  • Lastpage
    15
  • Abstract
    A method of noise variance estimation in BayesShrink image denoising is presented. The proposed approach competes with the well known MAD-based method and outperforms this method in more than 99% of our experimental results. The approach, called Residual Autocorrelation Power (RAP), provides a more accurate noise variance estimate and results in a smaller MSE.
  • Keywords
    Bayes methods; adaptive estimation; correlation methods; image denoising; mean square error methods; BayesShrink image denoising; MAD-based method; adaptive noise variance estimation; mean square error; median absolute deviation; residual autocorrelation power; BayesShrink image denoising; Median Absolute Deviation (MAD); noise variance estimation;
  • fLanguage
    English
  • Journal_Title
    Signal Processing Letters, IEEE
  • Publisher
    ieee
  • ISSN
    1070-9908
  • Type

    jour

  • DOI
    10.1109/LSP.2009.2030856
  • Filename
    5210207
    • Link To Document
    https://search.isc.ac/dl/search/defaultta.aspx?DTC=49&DC=1304877