A FUZZY SCHEME FOR IMAGE NOISE REDUCTION

Philippe Vautrot, Michel Herbin, Laurent Hussenet

2011

Abstract

The improvement of acquisition devices increases the need for processing of multicomponent images. In this context, the noise reduction is a preliminary preprocessing step affecting the results of the other image operations. This paper proposes a framework explaining usual noise reduction methods by the means of two fuzzy logic techniques: first a pixel fuzzification and second a defuzzification for estimating the filtered values. A new density-based filter is built for removing both impulse noise and Gaussian noise. The filter we propose is robust against outliers and it improves the classical bilateral approach for noise reduction of multicomponent images.

References

  1. Astola, J., Haavisto, P., and Neuovo, Y. (1990). Vector median filters. IEEE Proceedings, 78:678-689.
  2. Bouchon-Meunier, B. (1995). La logique floue et ses applications. Addison-Wesley, Paris.
  3. Bovik, A. (2000). Handbook of image and video processing. San Diego, CA, Academic Press.
  4. Camarena, J.-G., Gregori, V., Morillas, S., and Sapena, A. (2010). Two-step fuzzy logic-based method for impulse noise detection in colour images. Pattern Recognition Letters, 31:1842-1849.
  5. Detyniecki, M. (2001). Mathematical aggregation operators and their application to video querying. In Research Report, LIP6, PARIS.
  6. Gallegos-Funes, F. and Ponomaryov, V. (2004). Real-time image filtering scheme based on robust estimators in presence of impulsive noise. Real-Time Imaging, 10:69-80.
  7. Gonzales, R. and Woods, R. (1992). Digital Image Processing. Addison-Wesley, USA.
  8. Herbin, M. and Bonnet, N. (2002). A new adaptive kernel density estimation. In Information Processing and Management of Uncertainty (IPMU), Annecy.
  9. Kotropoulos, C. and Pitas, I. (2001). Nonlinear modelbased image/video processing and analysis. New York, NY, Wiley.
  10. Leekwijck, W. V. and Kerre, E. (1999). Defuzzification: criteria and classification. Fuzzy Sets System, 108(2):159-178.
  11. Lin, R. and Hsueh, Y. (2000). Multichannel filtering by gradient information. Signal Processing, 80:279-293.
  12. Lukac, R., Smolka, B., Plataniotis, K. N., and Venetsanopoulos, A. N. (2006). Vector sigma filters for noise detection and removal in color images. Journal of Visual Communication and Image Representation, 17:1-26.
  13. Morillas, S., Gregori, V., and Hervás, A. (2009). Fuzzy peer groups for reducing mixed gaussian-impulse noise from color images. IEEE Transactions on Image Processing, 18(7):1452-1466.
  14. Tomasi, C. and Manduchi, R. (1998). Bilateral filtering for gray and color images. In Proceedings of IEEE Conference on Computer Vision, Bombay, India.
  15. Ville, D. V. D., Nachtegael, M., der Weken, D. V., Kerre, E., Philips, W., and Lemahieu, I. (2003). Noise reduction by fuzzy image filtering. IEEE Transaction on Fuzzy Systems, 11(4):429-436.
  16. Wong, W., Chung, A., and Yu, S. (2004). Trilateral filtering for biomedical images. In IEEE proceedings.
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Paper Citation


in Harvard Style

Vautrot P., Herbin M. and Hussenet L. (2011). A FUZZY SCHEME FOR IMAGE NOISE REDUCTION . In Proceedings of the International Conference on Evolutionary Computation Theory and Applications - Volume 1: FCTA, (IJCCI 2011) ISBN 978-989-8425-83-6, pages 441-445. DOI: 10.5220/0003671604410445


in Bibtex Style

@conference{fcta11,
author={Philippe Vautrot and Michel Herbin and Laurent Hussenet},
title={A FUZZY SCHEME FOR IMAGE NOISE REDUCTION},
booktitle={Proceedings of the International Conference on Evolutionary Computation Theory and Applications - Volume 1: FCTA, (IJCCI 2011)},
year={2011},
pages={441-445},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0003671604410445},
isbn={978-989-8425-83-6},
}


in EndNote Style

TY - CONF
JO - Proceedings of the International Conference on Evolutionary Computation Theory and Applications - Volume 1: FCTA, (IJCCI 2011)
TI - A FUZZY SCHEME FOR IMAGE NOISE REDUCTION
SN - 978-989-8425-83-6
AU - Vautrot P.
AU - Herbin M.
AU - Hussenet L.
PY - 2011
SP - 441
EP - 445
DO - 10.5220/0003671604410445