PCL之滤波

直通滤波

直通滤波保留指定范围内部的点。

#include <iostream>
#include <pcl/point_types.h>
#include <pcl/filters/passthrough.h>

int main(int argc, char **argv)
{
    
    pcl::PointCloud<pcl::PointXYZ>::Ptr cloud(new pcl::PointCloud<pcl::PointXYZ>);
    pcl::PointCloud<pcl::PointXYZ>::Ptr cloud_filtered(new pcl::PointCloud<pcl::PointXYZ>);

    // Fill in the cloud data
    cloud->width = 5;
    cloud->height = 1;
    cloud->points.resize(cloud->width * cloud->height);

    for (auto &point : *cloud) //填充点云
    {
    
        point.x = 1024 * rand() / (RAND_MAX + 1.0f);
        point.y = 1024 * rand() / (RAND_MAX + 1.0f);
        point.z = 1024 * rand() / (RAND_MAX + 1.0f);
    }
    cloud->points[0].z = 1;//为了测试边界条件
    cloud->points[1].z = 0;

    std::cerr << "Cloud before filtering: " << std::endl;
    for (const auto &point : *cloud)
        std::cerr << " " << point.x << " "
                  << point.y << " "
                  << point.z << std::endl;

    // Create the filtering object
    //设置滤波器对象
    pcl::PassThrough<pcl::PointXYZ> pass;
    pass.setInputCloud(cloud);    //输入点云
    pass.setFilterFieldName("z"); //滤波字段
    //这里只保留 0.0 < z < 1.0的点云
    pass.setFilterLimits(0.0, 1.0); //设置过滤字段的范围
    //setFilterLimitsNegative默认设置为false。如果设置true，则表示setFilterLimits范围内的点滤掉
    //pass.setFilterLimitsNegative (true);
    pass.filter(*cloud_filtered); //执行过滤，并输出到cloud_filtered，但是输入的cloud不会变化

    std::cerr << "Cloud before filtering:cloud " << std::endl;
    for (const auto &point : *cloud)
        std::cerr << " " << point.x << " "
                  << point.y << " "
                  << point.z << std::endl;

    std::cerr << "Cloud after filtering: cloud_filtered" << std::endl;
    for (const auto &point : *cloud_filtered)
        std::cerr << " " << point.x << " "
                  << point.y << " "
                  << point.z << std::endl;

    return (0);
}

体素滤波下采样

#include <iostream>
#include <pcl/filters/voxel_grid.h>//体素滤波器头文件
#include <pcl/io/pcd_io.h> //PCD 读写类相关的头文件
#include <pcl/point_types.h> //点类型相关定义
#include <pcl/visualization/cloud_viewer.h> //点云可视化相关定义 可视化支持头文件
#include <pcl/common/common.h> //common模块，common.h的函数有pcl::getMinMax3D 
int main (int argc, char** argv)
{
    
	pcl::PointCloud<pcl::PointXYZ>::Ptr cloud(new pcl::PointCloud<pcl::PointXYZ>());
	pcl::PointCloud<pcl::PointXYZ>::Ptr cloud_filtered(new pcl::PointCloud<pcl::PointXYZ>());
  // 填入点云数据
    pcl::PCDReader reader;
  // 把路径改为自己存放文件的路径
 
    reader.read ("D:\\pclcode\\filter\\voxel_grid\\source\\table_scene_lms400.pcd", *cloud); //读取文件夹里面的table_scene_lms400.pcd点云文件
 
  //pcl::visualization::CloudViewer viewer("cloud viewer");//显示
  //viewer.showCloud(cloud);//显示cloud
  std::cerr << "PointCloud before filtering: " << cloud->width * cloud->height
	  << " data points (" << pcl::getFieldsList(*cloud) << ").";//输出滤波前点的总个数
  //system("pause");//暂停
  // 创建滤波器对象
  pcl::VoxelGrid<pcl::PointXYZ> sor;//创建滤波器对象
  sor.setInputCloud (cloud);//设置输入点云
  sor.setLeafSize (0.01f, 0.01f, 0.01f);//体素大小设置为10*10*10cm
  sor.filter (*cloud_filtered);//执行滤波，保存过滤结果在cloud_filtered
  std::cerr << "PointCloud after filtering: " << cloud_filtered->width * cloud_filtered->height 
       << " data points (" << pcl::getFieldsList (*cloud_filtered) << ").";//输出滤波后的总个数
  pcl::PCDWriter writer;//pcd写操作
  writer.write ("2f.pcd", *cloud_filtered);//将滤波后的点云存储在build文件夹里，并命名为2f.pcd
  //pcl::visualization::CloudViewer viewer("cloud viewer");//显示
  //viewer.showCloud(cloud_filterd);//显示cloud
  system("pause");//暂停
  return (0);
}
//PointCloud before filtering : 460400 data points(x y z).
//PointCloud after filtering : 41049 data points(x y z).
//请按任意键继续. . .