A taxonomy of similarity operators for color image filtering

Processing of color image data using directional information has received increased attention lately due to the introduction of the vector median and vector directional filters. These ranked-order type filters utilize the magnitude and the direction of color vectors to enhance, restore and segment color images. Their only tunable parameters are the size and shape of the sliding window, and the distance function used to measure similarity between the color vectors. The objective of this paper is two-fold. First, to present the different distance functions already in use and secondly, to introduce new measures that may be used in conjunction with ranked-order type filters for color image filtering. Simulation studies involving color images are used to assess the performance of the different filters.