🗒️点云滤波
2023-12-29
| 2023-12-31
Words 500Read Time≈ 2 min

VoxelGrid filter

用于降采样。
VoxelGrid可以看做是在输入点云数据中分割出的小方块，在每一个小方块中，计算点的均值完成降采样。

Statistical-Outlier-Removal filter

这种滤波主要是针对离群点的。
  1. 定义邻域大小K，表示距离某个点最近的K个点构成该点的邻域。
  1. 定义阈值T，如果偏差大于这个阈值，则认为该点是outlier。阈值T以第4步中全局标准差的倍数给出，例如1倍，2倍，3倍。
  1. 计算每个点到其邻域中的所有点的距离的均值。
  1. 假设所有的均值服从高斯分布，计算出全局的均值和标准差。
  1. 比较每个点的均值（第3步结果）和全局均值（第4步结果），如果差值大于阈值T，则滤除该点。
Removing outliers using a StatisticalOutlierRemoval filter — Point Cloud Library 0.0 documentation
In this tutorial we will learn how to remove noisy measurements, e.g. outliers, from a point cloud dataset using statistical analysis techniques.
Removing outliers using a StatisticalOutlierRemoval filter — Point Cloud Library 0.0 documentation
https://pcl.readthedocs.io/projects/tutorials/en/master/statistical_outlier.html#statistical-outlier-removal

Conditional-Removal filter & Radius-Outlier-Removal filter

Conditional-Removal filter

  1. 创建条件
  1. 验证每个点是否满足条件，若不满足，则滤除这个点
「注：greater than (GT), less than (LT)」

Radius-Outlier-Removal filter

  1. 设置搜索半径
  1. 设置邻域中点的数量的阈值
  1. 对每一个点，统计其搜索半径内的其他点的数量，如果数量低于阈值，则滤除这个点
Removing outliers using a Conditional or RadiusOutlier removal — Point Cloud Library 0.0 documentation
This document demonstrates how to remove outliers from a PointCloud using several different methods in the filter module. First we will look at how to use a ConditionalRemoval filter which removes all indices in the given input cloud that do not satisfy one or more given conditions. Then we will learn how to us a RadiusOutlierRemoval filter which removes all indices in its input cloud that don’t have at least some number of neighbors within a certain range.
Removing outliers using a Conditional or RadiusOutlier removal — Point Cloud Library 0.0 documentation
https://pcl.readthedocs.io/projects/tutorials/en/master/remove_outliers.html#remove-outliers

中值滤波

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