• DocumentCode
    1524065
  • Title

    Nonlinear filtering by threshold decomposition

  • Author

    Lin, Jean-Hsang ; Ansari, Nirwan ; Li, Jinhui

  • Author_Institution
    Comput. Commun. Lab., Ind. Technol. Res. Inst., Hsinchu, Taiwan
  • Volume
    8
  • Issue
    7
  • fYear
    1999
  • fDate
    7/1/1999 12:00:00 AM
  • Firstpage
    925
  • Lastpage
    933
  • Abstract
    A new threshold decomposition architecture is introduced to implement stack filters. The architecture is also generalized to a new class of nonlinear filters known as threshold decomposition (TD) filters which are shown to be equivalent to the class of L1-filters under certain conditions. Another new class of filters known as linear and order statistic (LOS) filters result from the intersection of the class of TD and L1-filters. Performance comparisons among several filters are then presented. It was found that TD is compatible with L1, LOS, and linear filters in suppressing Gaussian noise, and is superior in suppressing salt-and-pepper noise. LOS filters, however, provide a better compromise in performance and complexity
  • Keywords
    Gaussian noise; image processing; interference suppression; nonlinear filters; Gaussian noise suppression; L1-filters; LOS filters; TD filters; architecture; linear and order statistic filters; nonlinear filtering; salt-and-pepper noise; stack filters; threshold decomposition filters; AWGN; Additive noise; Additive white noise; Boolean functions; Computer architecture; Digital filters; Filtering; Finite impulse response filter; Gaussian noise; Nonlinear filters;
  • fLanguage
    English
  • Journal_Title
    Image Processing, IEEE Transactions on
  • Publisher
    ieee
  • ISSN
    1057-7149
  • Type

    jour

  • DOI
    10.1109/83.772235
  • Filename
    772235