Abstract
Image denoising is a well-known preprocessing step that can help for further processing tasks. With the increase of acquisition device performance, multicomponent images tend now to be widely used. To deal with, this paper proposes to describe usual noise reduction methods in the scope the fuzzy logic. The denoising process can be describe by a fuzzification step, some aggregations and a defuzzification step. To illustrate the concept, the bilateral filter is reformulated in the field of fuzzy logic. It is then extended to take into account impulse noise by using a density based function in the fuzzification step. This leads to a robust filter against outliers.
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References
Gonzales, R., Woods, R.: Digital Image Processing. Addison-Wesley, USA (1992)
Kotropoulos, C., Pitas, I.: Nonlinear model-based image/video processing and analysis. Wiley, New York (2001)
Bovik, A.: Handbook of image and video processing. Academic Press, San Diego (2000)
Lukac, R., Smolka, B., Plataniotis, K.N., Venetsanopoulos, A.N.: Vector sigma filters for noise detection and removal in color images. Journal of Visual Communication and Image Representation 17, 1–26 (2006)
Lin, R., Hsueh, Y.: Multichannel filtering by gradient information. Signal Processing 80, 279–293 (2000)
Wong, W., Chung, A., Yu, S.: Trilateral filtering for biomedical images. IEEE Proceedings (2004)
Gallegos-Funes, F., Ponomaryov, V.: Real-time image filtering scheme based on robust estimators in presence of impulsive noise. Real-Time Imaging 10, 69–80 (2004)
Ville, D.V.D., Nachtegael, M., der Weken, D.V., Kerre, E., Philips, W., Lemahieu, I.: Noise reduction by fuzzy image filtering. IEEE Transaction on Fuzzy Systems 11, 429–436 (2003)
Morillas, S., Gregori, V., Hervás, A.: Fuzzy peer groups for reducing mixed gaussian-impulse noise from color images. IEEE Transactions on Image Processing 18, 1452–1466 (2009)
Camarena, J.G., Gregori, V., Morillas, S., Sapena, A.: Two-step fuzzy logic-based method for impulse noise detection in colour images. Pattern Recognition Letters 31, 1842–1849 (2010)
Leekwijck, W.V., Kerre, E.: Defuzzification: criteria and classification. Fuzzy Sets System 108, 159–178 (1999)
Tomasi, C., Manduchi, R.: Bilateral filtering for gray and color images. In: Proceedings of IEEE Conference on Computer Vision, Bombay, India (1998)
Detyniecki, M.: Mathematical aggregation operators and their application to video querying. Research Report, LIP6, Paris (2001)
Bouchon-Meunier, B.: La logique floue et ses applications. Addison-Wesley, Paris (1995)
Astola, J., Haavisto, P., Neuovo, Y.: Vector median filters. IEEE Proceedings 78, 678–689 (1990)
Herbin, M., Bonnet, N.: A new adaptive kernel density estimation. In: Information Processing and Management of Uncertainty (IPMU), Annecy (2002)
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Vautrot, P., Herbin, M., Hussenet, L. (2013). A New Way to Describe Filtering Process Using Fuzzy Logic: Towards a Robust Density Based Filter. In: Madani, K., Dourado, A., Rosa, A., Filipe, J. (eds) Computational Intelligence. IJCCI 2011. Studies in Computational Intelligence, vol 465. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-35638-4_13
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DOI: https://doi.org/10.1007/978-3-642-35638-4_13
Publisher Name: Springer, Berlin, Heidelberg
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