1、先验知识

对灰度图像来说，img.step[0]代表图像一行的的长度：img.step[0]=img.cols;

img.step[1]代表图像一个元素的数据大小：img.step[0]=img.channels() ;

img.data: uchar的指针，指向Mat数据矩阵的首地址。

2、验证：通过地址访问元素

#include <iostream>
#include <opencv2/core.hpp>
#include <opencv2/highgui.hpp>
#include <opencv2/imgproc.hpp>
#include<vector>
#include<Eigen/Core>
#include <corecrt_math_defines.h>
using namespace std;
using namespace cv;int main()
{//生成一个3*4的矩阵Mat M = Mat::eye(3,4,CV_8UC1);cout << "M=\n" << M << endl;//访问第1行第1列的元素double sample11 = *(M.data+M.step[0]*0+M.step[1]*0);cout << "(1,1)=" << sample11 << endl;//访问第2行第2列的元素double sample22 = *(M.data+M.step[0]*1+M.step[1]*1);cout << "(2,2)=" << sample22 << endl;cout << "M.step[0]="<<M.step[0] << endl;cout << "M.step[1]="<<M.step[1] << endl;cv::waitKey(0);return 0;
}

3、隔点采样

#include <iostream>
#include <opencv2/core.hpp>
#include <opencv2/highgui.hpp>
#include <opencv2/imgproc.hpp>
#include<vector>
#include<Eigen/Core>
#include <corecrt_math_defines.h>
using namespace std;
using namespace cv;
#include "sift.h";Mat downSample(Mat src)
{Mat dst;if (src.channels() != 1)return src;if (src.cols <= 1 || src.rows <= 1){src.copyTo(dst);return dst;}dst.create((int)(src.rows / 2), (int)(src.cols / 2), src.type());cout << "-- " << dst.rows << " " << dst.cols << " --" << endl;int m = 0, n = 0;for (int i = 0; i < src.rows; i += 2, m++){n = 0;for (int j = 0; j < src.cols; j += 2, n++){//地址=首地址+cols*i+1*jdouble sample = *(src.data + src.step[0] * i + src.step[1] * j);//防止当图像长宽不一致时，长宽为奇数时，m,n越界if (m < dst.rows && n < dst.cols){*(dst.data + dst.step[0] * m + dst.step[1] * n) = sample;}}}return dst;
}int main() 
{double time0 = static_cast<double>(getTickCount());//记录起始时间Mat img = imread("D:\\VC\\c++\\opencv源码\\opencv源码\\Stereo_Sample\\ImageL1.jpg", IMREAD_GRAYSCALE);if (img.empty()){cout << "读取图像错误！" << endl;return 0;}siftLou k;Mat dst;dst = downSample(img);dst = downSample(dst);dst = downSample(dst);namedWindow("dst", WINDOW_FREERATIO);namedWindow("src", WINDOW_FREERATIO);imshow("dst", dst);imshow("src", img);cout << img.size() << endl;cout << dst.size() << endl;cout << "img.step[0]="<<img.step[0] << endl;cout << "img.step[1]=" << img.step[1] << endl;cout << "此方法运行时间：" << time0 << "秒" << endl;//输出运行时间cv::waitKey(0);return 0;
}