Anisotropic Denoising of 3D Point Clouds by Aggregation of Multiple Surface-Adaptive Estimates

Zhongwei Xu; Alessandro Foi

首页> 外文期刊>IEEE transactions on visualization and computer graphics >Anisotropic Denoising of 3D Point Clouds by Aggregation of Multiple Surface-Adaptive Estimates

【24h】

Anisotropic Denoising of 3D Point Clouds by Aggregation of Multiple Surface-Adaptive Estimates

机译：Anisotropic Denoising of 3D Point Clouds by Aggregation of Multiple Surface-Adaptive Estimates

获取原文

获取原文并翻译 | 示例

掌桥外文数据库（机构版） >>

开具论文收录证明 >>

文献代查 >>

页面导航

摘要
著录项
相关主题

摘要

3D point clouds commonly contain positional errors which can be regarded as noise. We propose a point cloud denoising algorithm based on aggregation of multiple anisotropic estimates computed on local coordinate systems. These local estimates are adaptive to the shape of the surface underlying the point cloud, leveraging an extension of the Local Polynomial Approximation (LPA) - Intersection of Confidence Intervals (ICI) technique to 3D point clouds. The adaptivity due to LPA-ICI is further strengthened by the dense aggregation with data-driven weights. Experimental results demonstrate state-of-the-art restoration quality of both sharp features and smooth areas.

著录项

来源
《IEEE transactions on visualization and computer graphics》 |2021年第6期|2851-2868|共18页
作者
Zhongwei Xu; Alessandro Foi;
展开▼
作者单位

Tampere University, Tampere, Finland;

Noiseless Imaging Oy (Ltd), Tampere, Finland;

展开▼
收录信息
原文格式 PDF
正文语种英语
中图分类模式识别与装置;
关键词
Three-dimensional displays; Noise reduction; Noise measurement; Estimation; Adaptation models; Approximation algorithms; Shape; 3D point cloud; denoising; anisotropic; surface-adaptive filtering;

Anisotropic Denoising of 3D Point Clouds by Aggregation of Multiple Surface-Adaptive Estimates

摘要

著录项

相关主题

期刊订阅