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Feature-preserving kernel diffusion for surface denoising
Conference proceeding

Feature-preserving kernel diffusion for surface denoising

Khaled Tarmissi, A. Ben Hamza and IEEE
2009 16th IEEE International Conference on Image Processing (ICIP), pp.2973-2976
11/2009
DOI: https://doi.org/10.1109/ICIP.2009.5414510

Abstract

anisotropic diffusion Anisotropic magnetoresistance Filtering Image edge detection Kernel kernel density Laplace equations Mesh denoising Noise reduction Rough surfaces Smoothing methods Surface fitting Surface roughness
We present a 3D mesh denoising method based on kernel density estimation. The proposed approach is able to reduce the over-smoothing effect and effectively remove undesirable noise while preserving prominent geometric features of a 3D mesh such as curved surface regions, sharp edges, and fine details. The experimental results demonstrate the effectiveness of the proposed approach in comparison to existing mesh denoising techniques.

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