Partial Differential Equations of Bivariate Median Filters

Abstract

Multivariate median filters have been proposed as generalisations of the well-established median filter for grey-value images to multi-channel images. As multivariate median, most of the recent approaches use the \(L^1\) median, i.e. the minimiser of an objective function that is the sum of distances to all input points. Many properties of univariate median filters generalise to such a filter. However, the famous result by Guichard and Morel about approximation of the mean curvature motion PDE by median filtering does not have a comparably simple counterpart for \(L^1\) multivariate median filtering. We discuss the affine equivariant Oja median as an alternative to \(L^1\) median filtering. We derive the PDE approximated by Oja median filtering in the bivariate case, and demonstrate its validity by a numerical experiment.