Adaptive filters for color image processing: A survey

Processing color images using nonlinear filters has received increased attention lately due to its importance in applications, such as multimedia technologies and telecommunications. The objective of this paper is twofold: (1) to introduce adaptive filtering techniques to the reader who is just beginning in this area and (2) to provide a review for the reader who may be well versed in nonlinear signal processing. The perspective of the topic offered here is one that comes primarily from work done in order statistics and adaptive filters for color image processing. Hence, many of the techniques and publications cited here relate to image filtering with the emphasis placed primarily on filtering algorithms based on fuzzy concepts, multidimensional scaling, and order statistics-based designs. It should be noted, however, that color image processing is a very broad field and thus contains many other approaches that have been developed from different perspectives, such as transform domain filtering, classical least-square approaches and neural networks, just to name a few. In this paper, we present a general formulation based on fuzzy concepts, which allows the use of adaptive weights in the filtering structure and we discuss different filter designs. The strong potential of fuzzy adaptive filters for color image processing is illustrated with several examples.