A New Fuzzy Impulse Noise Detection Method for Colour Images

  • Samuel Morillas
  • Stefan Schulte
  • Etienne E. Kerre
  • Guillermo Peris-Fajarnés
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 4522)


This paper focuses on fuzzy image denoising techniques. In particular, we develop a new fuzzy impulse noise detection method. The main difference between the proposed method and other state-of-the-art methods is the usage of the colour components for the impulse noise detection method that are used in a more appropriate manner. The idea is to detect all noisy colour components by observing the similarity between (i) the neighbours in the same colour band and (ii) the colour components of the two other colour bands. Numerical and visual results illustrate that the proposed detection method can be used for an effective noise reduction method.


  1. 1.
    Wang, J.H., Liu, W.J., Lin, L.D.: Histogram-Based Fuzzy Filter for Image Restoration. IEEE Transactions on Systems man and cybernetics part B.-cybernetics 32(2), 230–238 (2002)CrossRefMathSciNetGoogle Scholar
  2. 2.
    Schulte, S., Nachtegael, M., De Witte, V., Van der Weken, D., Kerre, E.E.: A Fuzzy Impulse Noise Detection and Reduction Method. IEEE Transactions on Image Processing 15(5), 1153–1162 (2006)CrossRefGoogle Scholar
  3. 3.
    Farbiz, F., Menhaj, M.B.: A fuzzy logic control based approch for image filtering. In: Kerre, E.E., Nachtegael, M. (eds.) Fuzzy Techniques in Image Processing. Studies in Fuzziness and Soft Computing, vol. 52, pp. 194–221. Physica, Heidelberg (2000)Google Scholar
  4. 4.
    Xu, H., Zhu, G., Peng, H., Wang, D.: Adaptive fuzzy switching filter for images corrupted by impulse noise. Pattern Recognition Letters 25, 1657–1663 (2004)CrossRefGoogle Scholar
  5. 5.
    Kalaykov, I., Tolt, G.: Real-time image noise cancellation based on fuzzy similarity. In: Nachtegael, M., Van der Weken, D., Van De Ville, D., Kerre, E.E. (eds.) Fuzzy Filters for Image Processing. Studies in Fuzziness and Soft Computing, vol. 122, pp. 54–71. Physica, Heidelberg (2003)Google Scholar
  6. 6.
    Schulte, S., De Witte, V., Nachtegael, M., Van der Weken, D., Kerre, E.E.: Fuzzy random impulse noise reduction method. Fuzzy Sets and Systems. In press (2007)Google Scholar
  7. 7.
    Schulte, S., De Witte, V., Nachtegael, M., Van der Weken, D., Kerre, E.E.: Fuzzy two-step filter for impulse noise reduction from color images. IEEE Transactions on Image Processing 15(11), 3567–3578 (2006)CrossRefGoogle Scholar
  8. 8.
    David, H.A., Nagaraja, H.N.: Order Statistics, 3rd edn. Wiley, New York (2003)zbMATHGoogle Scholar
  9. 9.
    Plataniotis, K.N., Venetsanopoulos, A.N.: Color Image Processing and Applications. Springer, Heidelberg (1998)Google Scholar
  10. 10.
    Lukac, R.: Adaptive vector median filtering. Pattern Recognition Letters 24(12), 1889–1899 (2003)CrossRefGoogle Scholar
  11. 11.
    Astola, J., Haavisto, P., Neuvo, Y.: Vector Median Filters. IEEE Proceedings 78(4), 678–689 (1990)CrossRefGoogle Scholar
  12. 12.
    Barni, M., Cappellini, V., Mecocci, A.: Fast vector median filter based on Euclidean norm approximation. IEEE Signal Processing Letters 1(6), 92–94 (1994)CrossRefGoogle Scholar
  13. 13.
    Lukac, R., Plataniotis, K.N., Venetsanopoulos, A.N., Smolka, B.: A statistically-switched adaptive vector median filter. Journal of Intelligent and Robotic Systems 42(4), 361–391 (2005)CrossRefGoogle Scholar
  14. 14.
    Camacho, J., Morillas, S., Latorre, P.: Efficient Impulse Noise suppression based on Statistical Confidence Limits. Journal of Imaging Science and Technology 50(5), 427–436 (2006)CrossRefGoogle Scholar
  15. 15.
    Smolka, B., Chydzinski, A.: Fast detection and impulsive noise removal in color images. Real-Time Imaging 11(5-6), 389–402 (2005)CrossRefGoogle Scholar
  16. 16.
    Hore, S., Qiu, B., Wu, H.R.: Improved vector filtering for color images using fuzzy noise detection. Optical Engineering 42(6), 1656–1664 (2003)CrossRefGoogle Scholar
  17. 17.
    Morillas, S., Gregori, V., Peris-Fajarnés, G., Latorre, P.: A fast impulsive noise color image filter using fuzzy metrics. Real-Time Imaging 11(5-6), 417–428 (2005)CrossRefGoogle Scholar
  18. 18.
    Lukac, R., Smolka, B., Martin, K., Plataniotis, K.N., Venetsanopoulos, A.N.: Vector filtering for color imaging. IEEE Signal Processing Magazine 22(1), 74–86 (2005)CrossRefGoogle Scholar
  19. 19.
    Garnett, R., Huegerich, T., Chui, C., He, W.: A universal noise removal algorithm with an impulse detector. IEEE Transactions on Image Processing 14(11), 1747–1754 (2005)CrossRefGoogle Scholar
  20. 20.
    Kerre, E.E.: Fuzzy sets and approximate Reasoning. Xian Jiaotong University Press (1998)Google Scholar
  21. 21.
    Lee, C.C.: Fuzzy logic in control systems: fuzzy logic controller-parts 1 and 2. IEEE Transactions on Systems, Man, and Cybernetics 20(2), 404–435 (1990)zbMATHCrossRefGoogle Scholar
  22. 22.
    Fodor, J.: A new look at fuzzy-connectives. Fuzzy sets and Systems 57(2), 141–148 (1993)zbMATHCrossRefMathSciNetGoogle Scholar

Copyright information

© Springer Berlin Heidelberg 2007

Authors and Affiliations

  • Samuel Morillas
    • 1
  • Stefan Schulte
    • 2
  • Etienne E. Kerre
    • 2
  • Guillermo Peris-Fajarnés
    • 1
  1. 1.Technical University of Valencia, E.P.S. de Gandia, Carretera Nazaret-Oliva s/n, 46730 Grao de GandiaSpain
  2. 2.Ghent University, Department of Applied Mathematics and Computer Science, Krijgslaan 281 - S9, 9000 GentBelgium

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