Fuzzy Impulse Noise Reduction Methods for Color Images Stefan Schulte, Mike Nachtegael, Val´ erie De Witte, Dietrich Van der Weken, and Etienne E. Kerre Summary. The reduction or removal of noise in a color image is an essential part of image processing, whether the final information is used for human perception or for an automatic inspection and analysis. In addition to all the classical based filters for noise reduction, many fuzzy inspired filters have been developed during the past years [3–26]. However, it is very difficult to judge the quality of all these different filters. For which noise types are they designed? How do they perform com- pared to each other? Are there some filters that clearly outperform the others? Do the numerical results correspond with the visual results? In this paper we answer these questions for color images that are corrupted with impulse noise. We also have developed a Java Applet (http://www.fuzzy.ugent.be/Dortmund.html). The Java Applet is used to compare all the mentioned filters with each other. It illustrates the numerical and visual performance of all these filters. Users have the possibility to load and corrupt an image from a predefined list. 1 Introduction Noise can be systematically introduced into digital images, e.g., due to the cir- cumstances of recording (e.g., dust on a lens, electronic noise in cameras and sensors, ...), transmission (e.g., interaction with satellite images, transmission over a channel, ...), scanning, etc. A fundamental problem of image processing is to reduce noise effectively from a digital image while keeping its features intact. Therefore, it is not surprising that different algorithms are developed for different noise types. During the past years, also a lot of fuzzy logic based filters have been introduced. In this article we will present a comparative study for color images (there already exist studies for grayscale images [1]). Besides this comparative study, we illustrate the shortcomings of the common filter techniques in order to stimulate researchers to design noise reduction techniques that reduce noise on the one hand and that preserve colors and image structures on the other hand. We also discuss some recent solutions that are especially designed for color images. These methods try to preserve the color component differences while performing efficient noise removal.