1.寻找图像中的最大值和最小值

#include <opencv2\opencv.hpp>
#include <iostream>
#include <vector>
using namespace std;
using namespace cv;
int main()
{
    system("color F0");  //更改输出界面颜色
    float a[12] = { 1, 2, 3, 4, 5, 10, 6, 7, 8, 9, 10, 0 };
    Mat img = Mat(3, 4, CV_32FC1, a);  //单通道矩阵
    Mat imgs = Mat(2, 3, CV_32FC2, a);  //多通道矩阵
    double minVal, maxVal;  //用于存放矩阵中的最大值和最小值
    Point minIdx, maxIdx;  ////用于存放矩阵中的最大值和最小值在矩阵中的位置
    /*寻找单通道矩阵中的最值*/
    minMaxLoc(img, &minVal, &maxVal, &minIdx, &maxIdx);
    cout << "img中最大值是：" << maxVal << "  " << "在矩阵中的位置:" << maxIdx << endl;
    cout << "img中最小值是：" << minVal << "  " << "在矩阵中的位置:" << minIdx << endl;
    /*寻找多通道矩阵中的最值*/
    Mat imgs_re = imgs.reshape(1, 4);  //将多通道矩阵变成单通道矩阵
    minMaxLoc(imgs_re, &minVal, &maxVal, &minIdx, &maxIdx);
    cout << "imgs中最大值是：" << maxVal << "  " << "在矩阵中的位置:" << maxIdx << endl;
    cout << "imgs中最小值是：" << minVal << "  " << "在矩阵中的位置:" << minIdx << endl;
    return 0;
}

2.计算图像的平均值和标准差

#include <opencv2\opencv.hpp>
#include <iostream>
#include <vector>
using namespace std;
using namespace cv;
int main()
{
    system("color F0");  //更改输出界面颜色
    float a[12] = { 1, 2, 3, 4, 5, 10, 6, 7, 8, 9, 10, 0 };
    Mat img = Mat(3, 4, CV_32FC1, a);  //单通道矩阵
    Mat imgs = Mat(2, 3, CV_32FC2, a);  //多通道矩阵
    cout << "/* 用meanStdDev同时求取图像的均值和标准差 */" << endl;
    Scalar myMean;
    myMean = mean(imgs);
    cout << "imgs均值=" << myMean << endl;
    cout << "imgs第一个通道的均值=" << myMean[0] << "    "
        << "imgs第二个通道的均值=" << myMean[1] << endl << endl;
    cout << "/* 用meanStdDev同时求取图像的均值和标准差 */" << endl;
    Mat myMeanMat, myStddevMat;
    meanStdDev(img, myMeanMat, myStddevMat);
    cout << "img均值=" << myMeanMat << "    " << endl;
    cout << "img标准差=" << myStddevMat << endl << endl;
    meanStdDev(imgs, myMeanMat, myStddevMat);
    cout << "imgs均值=" << myMeanMat << "    " << endl << endl;
    cout << "imgs标准差=" << myStddevMat << endl;
    return 0;
}

3.两图像的比较运算

#include <opencv2\opencv.hpp>
#include <iostream>
#include <vector>
using namespace std;
using namespace cv;
int main()
{
    float a[12] = { 1, 2, 3.3, 4, 5, 9, 5, 7, 8.2, 9, 10, 2 };
    float b[12] = { 1, 2.2, 3, 1, 3, 10, 6, 7, 8, 9.3, 10, 1 };
    Mat imga = Mat(3, 4, CV_32FC1, a);
    Mat imgb = Mat(3, 4, CV_32FC1, b);
    Mat imgas = Mat(2, 3, CV_32FC2, a);
    Mat imgbs = Mat(2, 3, CV_32FC2, b);
    //对两个单通道矩阵进行比较运算
    Mat myMax, myMin;
    max(imga, imgb, myMax);
    min(imga, imgb, myMin);
    //对两个多通道矩阵进行比较运算
    Mat myMaxs, myMins;
    max(imgas, imgbs, myMaxs);
    min(imgas, imgbs, myMins);
    //对两张彩色图像进行比较运算
    Mat img0 = imread("len.png");
    Mat img1 = imread("noobcv.jpg");
    if (img0.empty() || img1.empty())
    {
        cout << "请确认图像文件名称是否正确" << endl;
        return -1;
    }
    Mat comMin, comMax;
    max(img0, img1, comMax);
    min(img0, img1, comMin);
    imshow("comMin", comMin);
    imshow("comMax", comMax);
    //与掩模进行比较运算
    Mat src1 = Mat::zeros(Size(512, 512), CV_8UC3);
    Rect rect(100, 100, 300, 300);
    src1(rect) = Scalar(255, 255, 255);  //生成一个低通300*300的掩模
    Mat comsrc1, comsrc2;
    min(img0, src1, comsrc1);
    imshow("comsrc1", comsrc1);
    Mat src2 = Mat(512, 512, CV_8UC3, Scalar(0, 0, 255));  //生成一个显示红色通道的低通掩模
    min(img0, src2, comsrc2);
    imshow("comsrc2", comsrc2);
    //对两张灰度图像进行比较运算
    Mat img0G, img1G, comMinG, comMaxG;
    cvtColor(img0, img0G, COLOR_BGR2GRAY);
    cvtColor(img1, img1G, COLOR_BGR2GRAY);
    max(img0G, img1G, comMaxG);
    min(img0G, img1G, comMinG);
    imshow("comMinG", comMinG);
    imshow("comMaxG", comMaxG);
    waitKey(0);
    return 0;
}