1.Mat矩陣數值的儲存方式

            這裡以指標的方式訪問影象素為例

         (1)單通道

              定義一個單通道影象：

   cv::Mat img_1 = (320, 640, CV_8UC1, Scalar(0));

            對於單通道M(i,j)即為第i行j列的其灰度值；程式中表示為：

 img_1.ptr<uchar>(i)[j];

         (2)多通道

            這裡以RGB影象為例，每一個子列依次為B、G、R，，第一個分量是藍色，第二個是綠色，第三個是紅色。

           定義一個3通道BGR影象：

  cv::Mat img_1 = (320, 640, CV_8UC3, Scalar(0， 0 ，0));

           對於多通道M(i,j*3)即為第i行j列的B通道其灰度值，M(i,j*3+1) 即為第i行j列的G通道其灰度值，M(i,j*3+1) 即為第i行j列的B通     道其灰度值；程式中表示為：

                  第i行j列的B通道其灰度值：

    img_1.ptr<uchar>(i)[j*3];

                  第i行j列的G通道其灰度值：

 img_1.ptr<uchar>(i)[j*3+1];
 

                 第i行j列的R通道其灰度值：
                       

 img_1.ptr<uchar>(i)[j*3+2];

2.示例程式，以三種方法（指標，at，迭代器）

////獲得影象畫素值

#include <iostream>

#include <vector>

#include <algorithm>

#include <opencv2/core/core.hpp>

#include <opencv2/imgproc/imgproc.hpp>

#include <opencv2/opencv.hpp>


using namespace std;

using namespace cv;


void get_setImagePixel3(char *imagePath, int x, int y)

{

    Mat image = imread(imagePath, 1);

    //得寬高

    int w = image.cols;

    int h = image.rows;

    int channels = image.channels();



    if (channels == 1)

    {

        //得到初始位置的迭代器 

        Mat_<uchar>::iterator it = image.begin<uchar>();

        //得到終止位置的迭代器 

        Mat_<uchar>::iterator itend = image.end<uchar>();

        int pixel = *(it + y * w + x);

        cout << "灰度影象,處的灰度值為" << pixel << endl;

    }

    else

    {

        //得到初始位置的迭代器 

        Mat_<Vec3b>::iterator it = image.begin<Vec3b>();

        //得到終止位置的迭代器 

        Mat_<Vec3b>::iterator itend = image.end<Vec3b>();

        //讀取

        it = it + y * w + x;

        int b = (*it)[0];

        cout << b << endl;

        int g = (*it)[1];

        cout << g << endl;

        int r = (*it)[2];

        cout << r << endl;



        //設定畫素值

        (*it)[0] = 255;

        (*it)[1] = 255;

        (*it)[2] = 255;


    }

    imshow("cc", image);


}





int main()

{

    vector<int> v = {1,2,3,4,6};

   

    cout << "*********通過指標訪問畫素的灰度值********************"  << endl;

    //通過指標訪問畫素的灰度值

    //單通道

    Mat img1(20, 30, CV_32FC1, Scalar(0));

    img1.ptr<float>(19)[25] = 23456.1789;

    cout << "img(19,25):" << img1.ptr<float>(19)[25] <<endl;

    //多通道,建立一個B、G、R通道灰度值為0的影象，影象大小20*30，每個灰度值為16位無符號2進製表示

    Mat img2(20, 30, CV_16UC3, Scalar(0, 0, 0));

    cout << "img(1,2):" << int(img1.ptr<uchar>(19)[25]) << endl;


    Mat img = imread("test1.jpg");

    int numRow = img.rows;

    int numCol = img.cols;

    int numCol_channel = img.cols*img.channels();

    cout << "numRow:" << numRow << endl;

    cout << "numCol:" << numCol << endl;

    cout << "numCol_channel:" << numCol_channel << endl;

    cout << "45行，483列B通道灰度值" << int(img.ptr<uchar>(45)[483*3]) << endl;

    cout << "45行，483列G通道灰度值" << int(img.ptr<uchar>(45)[483*3+1]) << endl;

    cout << "45行，483列R通道灰度值" << int(img.ptr<uchar>(45)[483*3+2]) << endl;



Mat img_B(numRow, numCol, CV_8UC3, Scalar(0, 0, 0));

    Mat img_G(numRow, numCol, CV_8UC3, Scalar(0, 0, 0));

    Mat img_R(numRow, numCol, CV_8UC3, Scalar(0, 0, 0));

    for (int i = 0; i < numRow; i++)

    {

        for (int j = 0; j < numCol; j++)

        {

            img_B.ptr<uchar>(i)[j*3] = img.ptr<uchar>(i)[j*3];

            img_G.ptr<uchar>(i)[j*3+1] = img.ptr<uchar>(i)[j*3+1];

            img_R.ptr<uchar>(i)[j*3+2] = img.ptr<uchar>(i)[j*3+2];

        }

    }

    imshow("img", img);

    imshow("img_B", img_B);

    imshow("img_G", img_G);

    imshow("img_R", img_R);


    cout << endl;

    cout << endl;

    cout << endl;


    cout << "*********at只適合灰度值為8位的影象********************" << endl;

    //注意：at只適合灰度值為8位的影象

    //單通道

    Mat img3(20, 30, CV_8UC1, Scalar(0));

    cout << "img（7,8）" << int(img3.at<uchar>(7, 8)) << endl;

    //多通道

    Mat img4(20, 30, CV_8UC3, Scalar(0));

    //BGR通道

    cout << "B通道灰度值" << int(img4.at<Vec3b>(3, 4)[0]) << endl;

    cout << "G通道灰度值" << int(img4.at<Vec3b>(3, 4)[1]) << endl;

    cout << "R通道灰度值" << int(img4.at<Vec3b>(3, 4)[2]) << endl;


    waitKey(0);

    system("pause");

    return 0;

}