Please use this identifier to cite or link to this item:
Title: HLO : half-kernel laplacian operator for surface smoothing
Authors: Pan, Wei
Lu, Xuequan
Gong, Yuanhao
Tang, Wenming
Liu, Jun
He, Ying
Qiu, Guoping
Keywords: Computer Science - Computational Geometry
Computer Science - Graphics
Issue Date: 2020
Source: Pan, W., Lu, X., Gong, Y., Tang, W., Liu, J., He, Y. & Qiu, G. (2020). HLO : half-kernel laplacian operator for surface smoothing. Computer-Aided Design, 121, 102807-.
Project: RG26/17 
Journal: Computer-Aided Design 
Abstract: This paper presents a simple yet effective method for feature-preserving surface smoothing. Through analyzing the differential property of surfaces, we show that the conventional discrete Laplacian operator with uniform weights is not applicable to feature points at which the surface is non-differentiable and the second order derivatives do not exist. To overcome this difficulty, we propose a Half-kernel Laplacian Operator (HLO) as an alternative to the conventional Laplacian. Given a vertex v, HLO first finds all pairs of its neighboring vertices and divides each pair into two subsets (called half windows); then computes the uniform Laplacians of all such subsets and subsequently projects the computed Laplacians to the full-window uniform Laplacian to alleviate flipping and degeneration. The half window with least regularization energy is then chosen for v. We develop an iterative approach to apply HLO for surface denoising. Our method is conceptually simple and easy to use because it has a single parameter, i.e., the number of iterations for updating vertices. We show that our method can preserve features better than the popular uniform Laplacian-based denoising and it significantly alleviates the shrinkage artifact. Extensive experimental results demonstrate that HLO is better than or comparable to state-of-the-art techniques both qualitatively and quantitatively and that it is particularly good at handling meshes with high noise. We will make our source code publicly available.
ISSN: 0010-4485
DOI: 10.1016/j.cad.2019.102807
Schools: School of Computer Science and Engineering 
Rights: © 2019 Elsevier Ltd. All rights reserved.
Fulltext Permission: open
Fulltext Availability: With Fulltext
Appears in Collections:SCSE Journal Articles

Files in This Item:
File Description SizeFormat 
HLOhalf-kernel laplacian operator for surface smoothing.pdf11.16 MBAdobe PDFThumbnail

Citations 50

Updated on Jun 5, 2023

Web of ScienceTM
Citations 50

Updated on Jun 5, 2023

Page view(s)

Updated on Jun 8, 2023


Updated on Jun 8, 2023

Google ScholarTM




Items in DR-NTU are protected by copyright, with all rights reserved, unless otherwise indicated.