Non-Linear Gaussian Filters Performing Edge Preserving Diffusion

Abstract

This paper presents a new diffusion method for edge preserving smoothing of images. In contrast to other methods it is not based on an anisotropic modification of the heat conductance equation, rather on a modification of the way the solution of the heat conductance equation is obtained by convolving the initial data with a Gaussian kernel. Hence the method uses simple non-linear modifications of Gaussian filters, thus avoiding iteration steps and convergence problems. A chain of three to five filters with suitable parameters provides excellent smoothing of fine image details without destroying the coarser structures. The size and contrast of the eliminated details can be selected. The choice of the parameters is not critical and the edges are not displaced when changing the scale. The filter stages can be implemented efficiently on almost any parallel hardware architecture.