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Fast Surface Mesh Denoising with Regularization and Edge Preservation
Author(s) -
Huang Hui,
Ascher Uri
Publication year - 2007
Publication title -
pamm
Language(s) - English
Resource type - Journals
ISSN - 1617-7061
DOI - 10.1002/pamm.200700004
Subject(s) - polygon mesh , smoothing , vertex (graph theory) , noise reduction , cluster analysis , triangle mesh , a priori and a posteriori , laplacian smoothing , computer science , algorithm , enhanced data rates for gsm evolution , regularization (linguistics) , surface (topology) , mathematics , artificial intelligence , mesh generation , computer vision , geometry , computer graphics (images) , theoretical computer science , finite element method , graph , engineering , structural engineering , philosophy , epistemology
We describe a hybrid algorithm that is designed to smooth, but not only smooth, noisy polygonal surface meshes with sharp edges. While denoising, our method simultaneously regularizes triangle meshes on flat regions for further mesh processing and preserves edge sharpness for faithful reconstruction. A clustering technique, which combines K‐means and geometric a priori information, is first developed and refined. It is then used to implement vertex classification so that we can subsequently apply different smoothing operators on different vertex groups. This yields a highly efficient robust algorithm that is capable of handling both edge sharpness and mesh sampling irregularity without any significant cost increase. (© 2008 WILEY‐VCH Verlag GmbH & Co. KGaA, Weinheim)