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Robust denoising of point-sampled surfaces

Authors:

Renfang WangAuthors Info & Claims

WSEAS Transactions on Computers, Volume 8, Issue 1

Pages 153 - 162

Published: 01 January 2009 Publication History

Abstract

Based on sampling likelihood and feature intensity, in this paper, a feature-preserving denoising algorithm for point-sampled surfaces is proposed. In terms of moving least squares surface, the sampling likelihood for each point on point-sampled surfaces is computed, which measures the probability that a 3D point is located on the sampled surface. Based on the normal tensor voting, the feature intensity of sample point is evaluated. By applying the modified bilateral filtering to each normal, and in combination with sampling likelihood and feature intensity, the filtered point-sampled surfaces are obtained. Experimental results demonstrate that the algorithm is robust, and can denoise the noise efficiently while preserving the surface features.

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Cited By

Huang XTian QMao JJiang LLiang R(2018)The theory and application of an adaptive moving least squares for non-uniform samplesWSEAS Transactions on Computers10.5555/1852450.18524529:7(686-695)Online publication date: 17-Dec-2018
https://dl.acm.org/doi/10.5555/1852450.1852452
Huang XTian QMao JJiang LLiang R(2018)Adaptive moving least squares for scattering points fittingWSEAS Transactions on Computers10.5555/1852437.18524499:6(664-673)Online publication date: 17-Dec-2018
https://dl.acm.org/doi/10.5555/1852437.1852449

Index Terms

Robust denoising of point-sampled surfaces
1. Computing methodologies

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cover image WSEAS Transactions on Computers

WSEAS Transactions on Computers Volume 8, Issue 1

January 2009

193 pages

ISSN:1109-2750

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World Scientific and Engineering Academy and Society (WSEAS)

Stevens Point, Wisconsin, United States

Publication History

Published: 01 January 2009

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Cited By

Huang XTian QMao JJiang LLiang R(2018)The theory and application of an adaptive moving least squares for non-uniform samplesWSEAS Transactions on Computers10.5555/1852450.18524529:7(686-695)Online publication date: 17-Dec-2018
https://dl.acm.org/doi/10.5555/1852450.1852452
Huang XTian QMao JJiang LLiang R(2018)Adaptive moving least squares for scattering points fittingWSEAS Transactions on Computers10.5555/1852437.18524499:6(664-673)Online publication date: 17-Dec-2018
https://dl.acm.org/doi/10.5555/1852437.1852449

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