c++实现图像像素计算的示例详解

void cv::minMaxLoc(InputArray src,
                   double * minVal,
                   double * maxVal = 0,
                   Point * minLoc = 0,
                   Point * maxLoc = 0,
                   InputArray mask = noArray())

#include<iostream>
#include<vector>
#include<string>
#include <opencv2/opencv.hpp>
#include "opencv/highgui.h"
 
using namespace std;
using namespace cv;
 
int main(int argc,char** argv) {
    cout<<"OpenCv Version: "<<CV_VERSION<<endl;//输出使用的opencv版本号
    Mat img=imread('1.jpg');//单通道图像
    Mat imgs=imread("2.jpg");//多通道图像
    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的位置
 
    /*寻找单通道矩阵中的最值*/
    minMaxLoc(img,&maxVal,&minVal,&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 << "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;
    return 0;
}

cv::Scalar cv::mean(InputArray src,InputArray mask = noArray())

void cv::meanStdDev(InputArray src,OutputArray mean,OutputArray stddev,InputArray mask = noArray())

#include<iostream>
#include<vector>
#include<string>
#include <opencv2/opencv.hpp>
#include "opencv/highgui.h"
 
using namespace std;
using namespace cv;
 
int main(int argc,char** argv) {
    cout<<"OpenCv Version: "<<CV_VERSION<<endl;
    Mat img=imread("3.jpg");//单通道图像或矩阵
    Mat imgs=imread("4.jpg");//多通道图像或矩阵
 
    cout << "/* 用meanStdDev同时求取图像的均值和标准方差 */" << 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;
 
    cout << "/* 用meanStdDev同时求取图像的均值和标准方差 */" << endl;
    Mat myMeanMat,myStddevMat;
 
    meanStdDev(img,myMeanMat,myStddevMat);
    cout << "img均值=" << myMeanMat << " " << endl;
    cout << "img标准方差=" << myStddevMat << endl << endl;
    meanStdDev(imgs,myMeanMat,myStddevMat);
    cout << "img均值=" << myMeanMat << " " << endl;
    cout << "img标准方差=" << myStddevMat << endl << endl;
    return 0;
}

void cv::max(InputArray src1,InputArray src2,OutputArray dst) 
void cv::min(InputArray src1,InputArray src2,OutputArray dst)

#include<iostream>
#include<vector>
#include<string>
#include <opencv2/opencv.hpp>
#include "opencv/highgui.h"
 
using namespace std;
using namespace cv;
 
int main(int argc,char** argv) {
    cout<<"OpenCv Version: "<<CV_VERSION<<endl;
    //对两张彩色图像进行比较运算
    Mat img1=imread("l.png");
    Mat img2=imread("2.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(img1,img2,comMax);
    min(img1,img2,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);//起点（100，100）长300，宽300的矩形
    src1(rect)=Scalar(255,255,255);//生成一个300*300的掩模
    Mat comsrc1,comsrc2;
    min(img1,src1,comsrc1);
    imshow("comsrc1",comsrc1);
 
    Mat src2=Mat(512,512,CV_8UC3,Scalar(0,0,255));//生成一个显示红色的低通掩模
    min(img1,src2,comsrc2);
    imshow("comsrc2",comsrc2);
 
    //对两张图片灰度图像进行比较运算
    Mat img1g,img2g,comMing,comMaxg;
    cvtColor(img1,img1g,COLOR_BGR2GRAY);
    cvtColor(img2,img2g,COLOR_BGR2GRAY);
    max(img1g,img2g,comMaxg);
    max(img1g,img2g,comMaxg);
    imshow("comMing",comMing);
    imshow("comMaxg",comMaxg);
    return 0;
}

#include <opencv2\opencv.hpp>
#include <iostream>
#include <vector>
 
using namespace std;
using namespace cv;
 
int main()
{
   Mat img = imread("lena.png");
   if (img.empty())
  {
     cout << "请确认图像文件名称是否正确" << endl;
      return -1;
   }
   //创建两个黑白图像
  Mat img0 = Mat::zeros(200, 200, CV_8UC1);
  Mat img1 = Mat::zeros(200, 200, CV_8UC1);
  Rect rect0(50, 50, 100, 100);
  img0(rect0) = Scalar(255);//将起点50，50，长宽100的矩形框区域像素值置为255，白色
  Rect rect1(100, 100, 100, 100);
  img1(rect1) = Scalar(255);
  imshow("img0", img0);
  imshow("img1", img1);
  //进行逻辑运算
  Mat myAnd, myOr, myXor, myNot, imgNot;
  bitwise_not(img0, myNot);
  bitwise_and(img0, img1, myAnd);
  bitwise_or(img0, img1, myOr);
  bitwise_xor(img0, img1, myXor);
  bitwise_not(img, imgNot);
  imshow("myAnd", myAnd);
  imshow("myOr", myOr);
  imshow("myXor", myXor);
  imshow("myNot", myNot);
  imshow("img", img);
  imshow("imgNot", imgNot);
  waitKey(0);
  return 0;
  }