首先定义一个类函数,在类中定义用于接收回调函数的两个变量,用于在data_fusion函数中显示和处理.
两种不同类型消息: sensor_msgs::ImageConstPtr 图像消息; std_msgs::UInt16MultiArray::ConstPtr 向量消息

#include<ros/ros.h> //ros标准库头文件
#include<iostream> //C++标准输入输出库
#include<cv_bridge/cv_bridge.h> 
#include<sensor_msgs/image_encodings.h> 
#include<image_transport/image_transport.h> 
#include<opencv2/core/core.hpp>
#include<opencv2/highgui/highgui.hpp>
#include<opencv2/imgproc/imgproc.hpp>
#include"std_msgs/UInt16MultiArray.h"  
#include <stdio.h>
#include <stdlib.h>
#include <unistd.h>
using namespace std;
using namespace cv;

class SubscribeAndPublish
{
    
    

private:
  cv::Mat image; 
  std::vector<unsigned short> depth;

  ros::NodeHandle nh; 
  ros::Subscriber sub_rgb;
  ros::Subscriber sub_depth;  
public:  
  SubscribeAndPublish()
  {
    
    
    sub_rgb = nh.subscribe("/stereo_camera/RGB", 10, &SubscribeAndPublish::callback_rgb, this);
    sub_depth = nh.subscribe("/stereo_camera/disparity16", 10000, &SubscribeAndPublish::callback_depth, this);    
  }

  ~SubscribeAndPublish()
  {
    
    

  }

//相机的回调函数，这里的car_sensor是我自己的package,image_detect是自己定义的msg消息
 void callback_depth(const std_msgs::UInt16MultiArray::ConstPtr& msg) 
{
    
          
   depth = msg->data;    
    
}

void callback_rgb(const sensor_msgs::ImageConstPtr& msg)
{
    
    
   cv_bridge::CvImagePtr cv_ptr; // 声明一个CvImage指针的实例
   try   //对错误异常进行捕获，检查数据的有效性
    {
    
       
        //获得Mat类型图像数据   
       cv_ptr =  cv_bridge::toCvCopy(msg, sensor_msgs::image_encodings::BGR8); //将ROS消息中的图象信息提取，生成新cv类型的图象，复制给CvImage指针
       image=cv_ptr->image;       
      //  cv::imshow("INPUT", cv_ptr->image);
      //  cv::waitKey(25); 
    }
    catch(cv_bridge::Exception& e)  //异常处理
    {
    
    
        ROS_ERROR("cv_bridge exception: %s", e.what());
        return;
    }     
    data_fusion();
 }
   //我们在这里处理RGB图像和深度数据的融合
  void data_fusion()
  {
    
    
    if(image.empty())
    {
    
    
      std::cout<<"There is no image data in data_fusion!"<<std::endl;
    }
    else if(depth.size()==0)
    {
    
    
      std::cout<<"there is no depth image data in data_fusion!"<<std::endl;
    }
    //when we get both the image data and the depth data.we begin to do data-fusion
    else
    {
    
     
      int rows=720;
      int cols=1280;      
      Mat img(Size(rows,cols), CV_16UC1);  
      for (int i = 0; i <rows; ++i)
      {
    
    
          for (int j = 0; j < cols; ++j)
           {
    
    
              img.at<unsigned short>(j, i) =  depth[i * cols + j] ;
           }
      }        
      std::cout << "size():" << img[559930]<< std::endl;      
      cv::imshow("rgb_camera",image);
      cv::waitKey(10);
    }  
  }
};//End of class SubscribeAndPublish

int main(int argc, char **argv)
{
    
    
  //Initiate ROS
  ros::init(argc, argv, "stereo_camera_listener");
  //Create an object of class SubscribeAndPublish that will take care of everything
  SubscribeAndPublish image2depth;
  ros::spin(); 
  return 0;
}