Median filtering techniques for vector valued signals

Vector (multichannel) signal processing has arisen in the last decades as a major area of interest. The classical single-channel (scalar valued) processing techniques cannot deal with the interchannel dependencies, yielding to the development of new methods. This paper investigates two approaches to the median filtering of vector valued signals: filtering based on the reduced ordering in the space of signal samples and filtering with channel decorrelation. A novel filter is proposed that uses channel independentization by the central limit theorem. This filter performs better than classical filters in terms of mean square error measures and visual perception.