多尺度点云噪声检测的密度分析法

多尺度点云噪声检测的密度分析法

当前机载激光雷达数据和影像匹配得到的点云是密集点云数据的两类主要来源，但都不可避免存在着噪声点。本文提出一种新的点云去噪算法，可适用于这两类数据中所包含的噪声点的去除。算法主要包括两步: 第1步利用多尺度的密度算法去除孤立噪声和小的簇状噪声；第2步利用三角网约束将第1步中误检测为噪声的点重新归为正常点。针对真实数据进行了剔噪试验，结果表明本文提出的基于密度分析的多尺度噪声检测算法对孤立噪声和簇状噪声都有较为效，且对于质量较差的影像匹配点云的检测也能有效处理。本文算法检测率达到97%以上。...

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Veröffentlicht in:Ce hui xue bao 2015-03, Vol.44 (3), p.282
Hauptverfasser: 朱俊锋, 胡翔云, 张祖勋, 熊小东
Format: Artikel
Sprache:chi ; eng
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Airborne lasers
Data analysis
Density
Image processing
Image quality
Laser applications
Matching
Outliers (statistics)
Scanning
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container_issue 3
container_start_page 282
container_title Ce hui xue bao
container_volume 44
creator 朱俊锋
胡翔云
张祖勋
熊小东
description 当前机载激光雷达数据和影像匹配得到的点云是密集点云数据的两类主要来源，但都不可避免存在着噪声点。本文提出一种新的点云去噪算法，可适用于这两类数据中所包含的噪声点的去除。算法主要包括两步: 第1步利用多尺度的密度算法去除孤立噪声和小的簇状噪声；第2步利用三角网约束将第1步中误检测为噪声的点重新归为正常点。针对真实数据进行了剔噪试验，结果表明本文提出的基于密度分析的多尺度噪声检测算法对孤立噪声和簇状噪声都有较为效，且对于质量较差的影像匹配点云的检测也能有效处理。本文算法检测率达到97%以上。
doi_str_mv 10.11947/j.AGCS.2015.20130423
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subjects Airborne lasers
Data analysis
Density
Image processing
Image quality
Laser applications
Matching
Outliers (statistics)
Scanning
title 多尺度点云噪声检测的密度分析法
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