PCL creates depth image from point cloud

Constructing point cloud data

pcl::PointCloud<pcl::PointXYZ> pointcloud;
    for (float y = -0.5f; y <= 0.5f; y += 0.01f)
    {
        for (float z = -0.5f; z <= 0.5f; z += 0.01f)
        {
            pcl::PointXYZ point;
            point.x = 2.0 - y;
            point.y = y;
            point.z = z;
            pointcloud.points.push_back(point);
        }
    }
    pointcloud.width = (uint32_t)pointcloud.points.size();
    pointcloud.height = 1;

Create a depth image

    //定义参数
    float angularResolution = (float)(1.0f * (M_PI / 180.0f));//角分辨率是1度，也就是说由相邻像素表示的光束相差一弧度
    float maxAngleWidth = (float)(360.0f * (M_PI / 180.0f));
    float maxAngleHeight = (float)(180.0f * (M_PI / 180.0f));//模拟的范围传感器有一个完整的360度全景图
    Eigen::Affine3f sensorPose = (Eigen::Affine3f) Eigen::Translation3f(0.0f, 0.0f, 0.0f);//传感器的位置定义了虚拟传感器的6 DOF位置，它的原点是滚动=俯仰=偏航=0。
    pcl::RangeImage::CoordinateFrame coordinate_frame = pcl::RangeImage::CAMERA_FRAME;//x朝向右，y向下，z轴是向前的,另一种选择是激光框架，x面向前方，y向左，z向上。
    float noiseLevel = 0.00;//对于噪声，噪声是0，范围图像是使用普通的z缓冲区创建的
    float minRange = 0.0f;// minRange >0 ,所有更近的点都将被忽略
    int borderSize = 1;//边界大小>0,边界将会在裁剪时留下一个未被观察到的点的边界。

    pcl::RangeImage rangeImage;
    rangeImage.createFromPointCloud(pointcloud, angularResolution, maxAngleWidth, maxAngleHeight, sensorPose,
        coordinate_frame, noiseLevel, minRange, borderSize);

visualization

//以图像的形式显示深度图像，深度值作为颜色显示
    pcl::visualization::RangeImageVisualizer range_image_widget("Range image");
    range_image_widget.showRangeImage(rangeImage);

    std::cout << rangeImage << "\n";
    std::cout << pointcloud << "\n";
    pcl::visualization::PCLVisualizer::Ptr viewer(new pcl::visualization::PCLVisualizer("viewer"));
    pcl::visualization::PointCloudColorHandlerCustom<pcl::PointXYZ> colorhandler(pointcloud.makeShared(), 255, 0, 0);
    viewer->addPointCloud(pointcloud.makeShared(), colorhandler,"cloud");
    viewer->setBackgroundColor(1, 1, 1);
    viewer->setCameraPosition(
        0, 0, 0,
        0, 0, -1,
        0, 0, 0);
    viewer->addCoordinateSystem(1, "cloud");

Visualize the results

full code

#include "stdafx.h"
#include <iostream>
#include <pcl\visualization\pcl_plotter.h>
#include <pcl\visualization\pcl_visualizer.h>
#include <pcl\point_types.h>
#include <pcl\point_cloud.h>
#include <pcl\range_image\range_image.h>
#include <pcl\visualization\range_image_visualizer.h>
#include <vector>

int _tmain(int argc, _TCHAR* argv[])
{
    pcl::PointCloud<pcl::PointXYZ> pointcloud;
    for (float y = -0.5f; y <= 0.5f; y += 0.01f)
    {
        for (float z = -0.5f; z <= 0.5f; z += 0.01f)
        {
            pcl::PointXYZ point;
            point.x = 2.0 - y;
            point.y = y;
            point.z = z;
            pointcloud.points.push_back(point);
        }
    }
    pointcloud.width = (uint32_t)pointcloud.points.size();
    pointcloud.height = 1;

    //定义参数
    float angularResolution = (float)(1.0f * (M_PI / 180.0f));//角分辨率是1度，也就是说由相邻像素表示的光束相差一弧度
    float maxAngleWidth = (float)(360.0f * (M_PI / 180.0f));
    float maxAngleHeight = (float)(180.0f * (M_PI / 180.0f));//模拟的范围传感器有一个完整的360度全景图
    Eigen::Affine3f sensorPose = (Eigen::Affine3f) Eigen::Translation3f(0.0f, 0.0f, 0.0f);//传感器的位置定义了虚拟传感器的6 DOF位置，它的原点是滚动=俯仰=偏航=0。
    pcl::RangeImage::CoordinateFrame coordinate_frame = pcl::RangeImage::CAMERA_FRAME;//x朝向右，y向下，z轴是向前的,另一种选择是激光框架，x面向前方，y向左，z向上。
    float noiseLevel = 0.00;//对于噪声，噪声是0，范围图像是使用普通的z缓冲区创建的
    float minRange = 0.0f;// minRange >0 ,所有更近的点都将被忽略
    int borderSize = 1;//边界大小>0,边界将会在裁剪时留下一个未被观察到的点的边界。

    pcl::RangeImage rangeImage;
    rangeImage.createFromPointCloud(pointcloud, angularResolution, maxAngleWidth, maxAngleHeight, sensorPose,
        coordinate_frame, noiseLevel, minRange, borderSize);

    //以图像的形式显示深度图像，深度值作为颜色显示
    pcl::visualization::RangeImageVisualizer range_image_widget("Range image");
    range_image_widget.showRangeImage(rangeImage);

    std::cout << rangeImage << "\n";
    std::cout << pointcloud << "\n";
    pcl::visualization::PCLVisualizer::Ptr viewer(new pcl::visualization::PCLVisualizer("viewer"));
    pcl::visualization::PointCloudColorHandlerCustom<pcl::PointXYZ> colorhandler(pointcloud.makeShared(), 255, 0, 0);
    viewer->addPointCloud(pointcloud.makeShared(), colorhandler,"cloud");
    viewer->setBackgroundColor(1, 1, 1);
    viewer->setCameraPosition(
        0, 0, 0,
        0, 0, -1,
        0, 0, 0);
    viewer->addCoordinateSystem(1, "cloud");
    while (!viewer->wasStopped())
    {
        viewer->spinOnce();
    }
    system("pause");
    return 0;
}

Reference
[1]. http://pointclouds.org/documentation/tutorials/range_image_creation.php#range-image-creation