Alternative distance/similarity measures for reduced ordering based nonlinear vector filters

Reduced ordering based nonlinear vector filters have proved successful in removing long-tailed noise from color images while preserving edges and fine image details. These filters commonly utilize variants of the Minkowski distance to order the color vectors with the aim of distinguishing between noisy and noise-free vectors. In this paper, we review various alternative distance measures and evaluate their performance on a large and diverse set of images. The results demonstrate that there are in fact strong alternatives to the popular Minkowski metrics.