Combining vector median and vector directional filters: the directional-distance filters

It is generally accepted that multispectral image processing should be employed using a vector approach. Two are the main classes of vector processing filters that have been reported in the literature. Astola et al. (1990) introduce the well known class of vector median filters (VMF), which are derived as MLE estimates from exponential distributions. Trahanias et al. (see IEEE Trans. Image Process., vol.2, p.528-34, Oct. 1993) study the processing of color image data using directional information, considering the class of vector directional filters (VDF). We introduce a new class of filters, the directional-distance filters (DDF), which combine both VDF and VMF in a novel way. We show that DDF can eliminate the noise much more effectively than the VMF (even the impulsive noise), and that they have the property of chromaticity preservation