• DocumentCode
    872625
  • Title

    A fuzzy operator for the enhancement of blurred and noisy images

  • Author

    Russo, Fabrizio ; Ramponi, Giovanni

  • Author_Institution
    Dipartimento di Elettrotecnica Elettronica ed Inf., Trieste Univ., Italy
  • Volume
    4
  • Issue
    8
  • fYear
    1995
  • fDate
    8/1/1995 12:00:00 AM
  • Firstpage
    1169
  • Lastpage
    1174
  • Abstract
    Rule-based fuzzy operators are a novel class of operators specifically designed in order to apply the principles of approximate reasoning to digital image processing. This paper shows how a fuzzy operator that is able to perform detail sharpening but is insensitive to noise can be designed. The results obtainable by the proposed technique in the enhancement of a real image are presented
  • Keywords
    fuzzy set theory; image enhancement; inference mechanisms; knowledge based systems; noise; approximate reasoning; blurred images; detail sharpening; digital image processing; image enhancement; noisy images; rule-based fuzzy operators; Digital images; Fuzzy reasoning; Fuzzy set theory; Fuzzy sets; Humans; Image enhancement; Image processing; Pattern recognition; Pixel; Smoothing methods;
  • fLanguage
    English
  • Journal_Title
    Image Processing, IEEE Transactions on
  • Publisher
    ieee
  • ISSN
    1057-7149
  • Type

    jour

  • DOI
    10.1109/83.403425
  • Filename
    403425