opencv图像对比度

// 处理图片的对比度.cpp: 定义控制台应用程序的入口点。
//

# include "stdafx.h"
#include "opencv2/opencv.hpp"
#include   
#include "iostream"
using namespace std;
using namespace cv;

int main()
{
    //方式1：手动处理
    Mat src, dest;
    src = imread("lena.jpg");
    if (src.empty()) {
        cout << "error";
        return -1;
    }
    dest = Mat::zeros(src.size(), src.type());
    int cols =  src.cols * src.channels();
    int offsetx = src.channels();
    int rows = src.rows;
    cout << cols<< "---" << rows << "---" << offsetx << endl;
    for (int row = 1; row < rows - 1; row++) {
        const uchar* current = src.ptr(row-1);//当前的指针所代表的像素
        const uchar* previous = src.ptr(row);//前一帧所代表的像素
        const uchar* next = src.ptr(row+1);//下一帧所代表的像素
        uchar* output = dest.ptr(row);//目标对象像素
        for (int col = offsetx; col < cols; col++ ) {
            //带入目标公式current[col - offsetx]代表前一个current[col + offsetx]后面一个previous[col]正对着next[col]正对着（正对着代表列一样），同理前面的列不一样
            // saturate_cast // 函数代表把像素范围控制在0-255之内
              output[col] = saturate_cast(5 * current[col] - (current[col - offsetx] + current[col + offsetx] + previous[col] + next[col]));
        }
    }

    namedWindow("src");
    imshow("src", src);

    namedWindow("dest");
    imshow("dest",dest);


    //方式2
    double start = getTickCount();
    Mat dest2;
    dest2 = Mat::zeros(src.size(), src.type());
    Mat kernel = (Mat_<char>(3, 3) << 0, -1, 0, -1, 5, -1, 0, -1, 0);
    filter2D(src, dest2, src.depth(), kernel);
    double sum = (getTickCount() - start) / getTickFrequency();
    printf("%.2f",sum);
    namedWindow("dest2");
    imshow("dest2", dest2);

    waitKey();
    return 0;
}

原图:

方式1：

方式2：