PDE Evolutions for M-Smoothers in One, Two, and Three Dimensions
Martin Welk, Joachim Weickert

TL;DR
This paper derives PDE models from local M-smoothers in multiple dimensions, revealing new insights into mode filtering and sharpening effects, and proposes a stable numerical scheme for their simulation.
Contribution
It introduces a family of PDEs from M-smoothers for 1D, 2D, and 3D, extending the understanding of mode filtering and sharpening in image processing.
Findings
PDEs for p<1 exhibit sharpening properties.
Mode filtering occurs as p approaches -1, not zero.
The proposed finite difference scheme is stable and rotation invariant.
Abstract
Local M-smoothers are interesting and important signal and image processing techniques with many connections to other methods. In our paper we derive a family of partial differential equations (PDEs) that result in one, two, and three dimensions as limiting processes from M-smoothers which are based on local order- means within a ball the radius of which tends to zero. The order may take any nonzero value , allowing also negative values. In contrast to results from the literature, we show in the space-continuous case that mode filtering does not arise for , but for . Extending our filter class to -values smaller than allows to include e.g. the classical image sharpening flow of Gabor. The PDEs we derive in 1D, 2D, and 3D show large structural similarities. Since our PDE class is highly anisotropic and may contain backward parabolic operators,…
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