SBL Mesh Filter: A Fast Separable Approximation of Bilateral Mesh Filtering
Guillaume Vialaneix and Tamy Boubekeur Vision, Modeling and Visualization 2011
We develop a separable approach based on restricted neigborhood gathered along curvature directions. We compare 3 different variants of the algorithm against exact, full resolution bilateral fitlering and demonstrate a significant speed up for a negligeable error. Our approach is simple, easy to implement on any bilateral mesh filter and can be generalized to other types of local filters.
Abstract
Bilateral mesh filtering is a simple and powerful feature-preserving
filtering operator which allows to smooth or remove noise from surface
meshes while preserving important features in a non-iterative
way. However, to be effective, such a filter may require quite a large
support size, inducing slow processing when applied on high resolution
meshes such as the ones produced by automatic 3D acquisition devices. In
this paper, we propose a separable approximation of bilateral mesh
filtering based on a local decomposition of the bi-dimensional filter
into a product of two one-dimensional ones. In particular, we show that
this approximation leads to piecewise smooth surfaces which are very
close to the ones produced by the exact filter, using only a fraction of
the usual required time. Compared to bilateral image filtering, the main
problem here is to find meaningful directions at every point to orient
the two one-dimensional filters. Our solution exploits the minimum and
maximum curvature directions at each point and demonstrates a
significant speed-up on meshes ranging from thousands to millions of
elements, enabling feature-preserving filtering with large support size
in a variety of practical scenarii. Our approach is simple, easy to
implement and orthogonal to other
kinds of optimizations such as higher dimensional clustering using a
bilateral grid or a Gaussian
kd-tree and can therefore be combined to them to reach even higher performance.
Resources
BibTex Reference: @inproceedings{Vialaneix:2011:SBL,
author = {Guillaume Vialaneix and Tamy Boubekeur},
title = {SBL Mesh Filter: A Fast Separable Approximation of Bilateral Mesh Filtering},
booktitle = {Vision, Modeling and Visualization (VMV) 2011},
year = {2011},
}
