A new fuzzy additive noise reduction method

Authors:
Stefan Schulte;Valérie De Witte;Mike Nachtegael;Tom Mélange;Etienne E. Kerre
Affiliations:
Department of Applied Mathematics and Computer Science, Ghent University, Gent, Belgium;Department of Applied Mathematics and Computer Science, Ghent University, Gent, Belgium;Department of Applied Mathematics and Computer Science, Ghent University, Gent, Belgium;Department of Applied Mathematics and Computer Science, Ghent University, Gent, Belgium;Department of Applied Mathematics and Computer Science, Ghent University, Gent, Belgium
Venue:
ICIAR'07 Proceedings of the 4th international conference on Image Analysis and Recognition
Year:
2007

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Abstract

In this paper we present a new alternative noise reduction method for color images that were corrupted with additive Gaussian noise. We illustrate that color images have to be processed in a different way than most of the state-of-the-art methods. The proposed method consists of two sub-filters. The main concern of the first subfilter is to distinguish between local variations due to noise and local variations due to image structures such as edges. This is realized by using the color component distances instead of component differences as done by most current filters. The second subfilter is used as a complementary filter which especially preserves differences between the color components. This is realized by calculating the local differences in the red, green and blue environment separately. These differences are then combined to calculate the local estimation of the central pixel. Experimental results show the feasibility of the proposed approach.