  This paper deals with an improvement of vertex based nonlinear diffusion for
mesh denoising. This method directly filters the position of the vertices using
Laplace, reduced centered Gaussian and Rayleigh probability density functions
as diffusivities. The use of these PDFs improves the performance of a
vertex-based diffusion method which are adapted to the underlying mesh
structure. We also compare the proposed method to other mesh denoising methods
such as Laplacian flow, mean, median, min and the adaptive MMSE filtering. To
evaluate these methods of filtering, we use two error metrics. The first is
based on the vertices and the second is based on the normals. Experimental
results demonstrate the effectiveness of our proposed method in comparison with
the existing methods.
