请使用cvtColor()函数、resize函数、cv_bridge函数，给出ubantu系统下将ros仿真摄像头图像输出为灰度图并降低分辨率的.cpp文件，同时给出其编译方法

下面是将ROS仿真摄像头图像输出为灰度图并降低分辨率的cpp代码：

#include <ros/ros.h>
#include <sensor_msgs/Image.h>
#include <cv_bridge/cv_bridge.h>
#include <opencv2/opencv.hpp>
#include <image_transport/image_transport.h>

const int WIDTH = 320;
const int HEIGHT = 240;

void imageCallback(const sensor_msgs::Image::ConstPtr& msg)
{
    cv::Mat image;
    cv_bridge::CvImagePtr cv_ptr;
    try
    {
        cv_ptr = cv_bridge::toCvCopy(msg, sensor_msgs::image_encodings::BGR8);
        cv::cvtColor(cv_ptr->image, image, CV_BGR2GRAY); // 将图像转为灰度图
        cv::resize(image, image, cv::Size(WIDTH, HEIGHT)); // 降低分辨率
    }
    catch (cv_bridge::Exception& e)
    {
        ROS_ERROR("cv_bridge exception: %s", e.what());
        return;
    }

    // 显示图像
    cv::imshow("image", image);
    cv::waitKey(1);
}

int main(int argc, char **argv)
{
    ros::init(argc, argv, "camera_subscriber");
    ros::NodeHandle nh;

    cv::namedWindow("image");

    image_transport::ImageTransport it(nh);
    image_transport::Subscriber sub = it.subscribe("/camera/image_raw", 1, imageCallback);

    ros::spin();

    cv::destroyWindow("image");

    return 0;
}

编译方法：

1. 在ROS工作空间的src目录下创建一个新的package：`catkin_create_pkg image_subscriber roscpp sensor_msgs cv_bridge image_transport opencv2`
2. 在package目录下创建一个新的cpp文件：`image_subscriber.cpp`
3. 在CMakeLists.txt中添加以下内容：

find_package(OpenCV REQUIRED)
include_directories(${OpenCV_INCLUDE_DIRS})

add_executable(image_subscriber src/image_subscriber.cpp)
target_link_libraries(image_subscriber ${OpenCV_LIBRARIES} ${catkin_LIBRARIES})

4. 在terminal中进入ROS工作空间的根目录，执行`catkin_make`命令进行编译

注：需将以上代码保存在`image_subscriber.cpp`文件中，并将其放置于`src`文件夹下。