Producing negative of a grayscale image: C++ and OpenCV

Theory
The concept behind negative of grayscale image is very simple. Just subtract each intensity level of an image from 255. The negative transformation is given by the function
                         s = L – 1 – r
Where s is the pixel after transformation, r is the pixel before transformation and L is the maximum intensity level (in our case it is 256).

Program
The program is written in C++ using OpenCV library in QT IDE. If you are using QT IDE then add the following line of code in .pro file.

INCLUDEPATH += /usr/include/opencv/
CONFIG += link_pkgconfig
PKGCONFIG += opencv
LIBS += -Icv -Ihighhui

#include <opencv/cv.h>
#include <opencv2/core/core.hpp>
#include <opencv2/highgui/highgui.hpp>
using namespace cv;
 
int main()
{
    //read the image in matrix image
    Mat image = imread("charlie.jpg");
 
    // initialize the output matrix with zeros
    Mat new_image = Mat::zeros( image.size(), image.type() );
 
    // create a matrix with all elements equal to 255 for subtraction
    Mat sub_mat = Mat::ones(image.size(), image.type())*255;
 
    //subtract the original matrix by sub_mat to give the negative output new_image
    subtract(sub_mat, image, new_image);
 
     // Create Windows
     namedWindow("Original Image", 1);
     namedWindow("New Image", 1);
 
     // Show stuff
     imshow("Original Image", image);
     imshow("New Image", new_image);
 
     // Wait until user press some key
     waitKey();
     return 0;
}

Output