• DocumentCode
    3399386
  • Title

    Fuzzy Filters for Noise Reduction: The Case of Gaussian Noise

  • Author

    Nachtegael, M. ; Schulte, S. ; Van der Weken, D. ; De Witte, V. ; Kerre, E.E.

  • Author_Institution
    Dept. of Appl. Math. & Comput. Sci., Ghent Univ., Gent
  • fYear
    2005
  • fDate
    25-25 May 2005
  • Firstpage
    201
  • Lastpage
    206
  • Abstract
    Noise reduction is a well-known problem in image processing. The reduction of noise in an image sometimes is as a goal itself, and sometimes is considered as a pre-processing step. Besides the classical filters for noise reduction, quite a lot of fuzzy inspired filters have been proposed during the past years. However, it is very difficult to judge the quality of this wide variety of filters. For which noise types are they designed? How do they perform for those noise types? How do they perform compared to each other? Can we select filters that clearly outperform the others? Is there a difference between numerical and visual results? In this paper, we answer these questions for images that are corrupted with Gaussian noise
  • Keywords
    Gaussian noise; filtering theory; fuzzy set theory; image denoising; Gaussian noise; fuzzy filters; image processing; noise reduction; Computer aided software engineering; Electromagnetic interference; Filters; Fuzzy logic; Fuzzy sets; Gaussian noise; Gray-scale; Image processing; Image storage; Noise reduction;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Fuzzy Systems, 2005. FUZZ '05. The 14th IEEE International Conference on
  • Conference_Location
    Reno, NV
  • Print_ISBN
    0-7803-9159-4
  • Type

    conf

  • DOI
    10.1109/FUZZY.2005.1452393
  • Filename
    1452393