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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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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