2010/09/23 by Mohammed El Hassouni, Mohammed EL Hassouni, Hassouni, Mohammed EL +2
Computer Science · Engineering · #3D Shape Modeling and Analysis #Advanced Numerical Analysis Techniques #Computer Graphics and Visualization Techniques #Computer Vision and Pattern Recognition (cs.CV) #FOS: Computer and information sciences #cs.CV
paper · pdf · doi:10.48550/arxiv.1009.4581
arxiv created 2010/09/23 · openalex publication_date 2010/09/23 · arxiv updated 2010/09/24 · openalex created_date 2025/10/10 · openalex updated_date 2026/07/28
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.