• DocumentCode
    1349061
  • Title

    Noise suppression by removing singularities

  • Author

    Shekarforoush, H.

  • Author_Institution
    Center for Autom. Res., Maryland Univ., College Park, MD, USA
  • Volume
    48
  • Issue
    7
  • fYear
    2000
  • fDate
    7/1/2000 12:00:00 AM
  • Firstpage
    2175
  • Lastpage
    2179
  • Abstract
    A method is proposed for suppressing Gaussian noise by extracting local singularities. The method is based on truncating Riemann series decomposition, whose components naturally characterize different orders of Holder regularity. The approach yields a single-step filtering technique whose performance is comparable to three-step wavelet decomposition and thresholding techniques
  • Keywords
    Gaussian noise; filtering theory; interference suppression; Gaussian noise suppression; Holder regularity; Riemann series decomposition; local singularities extraction; single-step filtering technique; three-step wavelet decomposition; thresholding techniques; Covariance matrix; Filtering; Gaussian noise; Interference; Maximum likelihood detection; Noise robustness; Random processes; Signal processing algorithms; Testing; Training data;
  • fLanguage
    English
  • Journal_Title
    Signal Processing, IEEE Transactions on
  • Publisher
    ieee
  • ISSN
    1053-587X
  • Type

    jour

  • DOI
    10.1109/78.847805
  • Filename
    847805
    • Link To Document
    https://search.isc.ac/dl/search/defaultta.aspx?DTC=49&DC=1349061