The principle is simple. Five times the value of a red pixel minus the sum of the values of four green pixels is used as the pixel value of a new red pixel.

The whole picture is traversed and modeled once in accordance with this method.

First, the concrete underlying principle code is as follows:

#include <opencv.hpp>
#include <iostream>
#include <math.h>
#include <opencv2/highgui/highgui_c.h>


using namespace cv;

int main(int argc, char** argv) {
    Mat src, dst;
    src = imread("L:/4.jpg");
    if (!src.data) {
        printf("could not load image...\n");
        return -1;
    }
    namedWindow("input image", CV_WINDOW_AUTOSIZE);
    imshow("input image", src);


    int cols = (src.cols - 1) * src.channels();
    int offsetx = src.channels();
    int rows = src.rows;

    dst = Mat::zeros(src.size(), src.type());  //Zero Matrix of the Same Size and Type as the Original Photo
    for (int row = 1; row < (rows - 1); row++) {
        const uchar* previous = src.ptr<uchar>(row - 1);
        const uchar* current = src.ptr<uchar>(row);
        const uchar* next = src.ptr<uchar>(row + 1);
        uchar* output = dst.ptr<uchar>(row);
        for (int col = offsetx; col < cols; col++) {
            output[col] = saturate_cast<uchar>(5 * current[col] - (current[col - offsetx] + current[col + offsetx] + previous[col] + next[col]));  //Core part
        }
    }

    namedWindow("contrast image demo", CV_WINDOW_AUTOSIZE);
    imshow("contrast image demo", dst);

    waitKey(0);
    return 0;
}

The core part of the program involves pointer issues:

Pixel boundary value processing problem:

2. Calling opencv's core directly

#include <opencv.hpp>
#include <iostream>
#include <math.h>
#include <opencv2/highgui/highgui_c.h>


using namespace cv;

int main(int argc, char** argv) {
    Mat src, dst;
    src = imread("L:/4.jpg");
    if (!src.data) {
        printf("could not load image...\n");
        return -1;
    }
    namedWindow("input image", CV_WINDOW_AUTOSIZE);
    imshow("input image", src);
    
    double t = getTickCount();
    Mat kernel = (Mat_<char>(3, 3) << 0, -1, 0, -1, 5, -1, 0, -1, 0);
    filter2D(src, dst, src.depth(), kernel);
    double timeconsume = (getTickCount() - t) / getTickFrequency();
    printf("tim consume %.2f\n", timeconsume);

    namedWindow("contrast image demo", CV_WINDOW_AUTOSIZE);
    imshow("contrast image demo", dst);

    waitKey(0);
    return 0;
}

The main changes in code are

Other heads and tails remain unchanged

The principle and effect of one and two codes are exactly the same. The results are as follows:

Original image:

Enhanced image:

Look at the railings behind the car, the effect is still very obvious.