访问图像像素的常见方式

#include <opencv2/opencv.hpp>
#include <opencv2/core/core.hpp>
#include <iostream>
using namespace std;
using namespace cv;
int main()
{
//1，最快方式，利用 C[]
 Mat src = imread("D:/Code/image/1.jpg");
 Mat dst = src.clone();
 int rowNum = dst.rows;
 int colNum = dst.cols * dst.channels();
 int divideWidth = 50; //颜色间隔大小
 imshow("输入图像", src);
 for (int i = 0; i < rowNum; i++)
 {
      uchar* data = dst.ptr<uchar>(i); // 获取第i行的首地址
      for (int j = 0; j < colNum; j++)
      {
       data[j] = data[j] / divideWidth * divideWidth + divideWidth / 2; //处理每个像素方式
      }
 }
 imshow("效果图", dst);
 waitKey(6000);
 return 0;
}

//2，最简洁方式，利用动态地址运算配合at方法
for (int i = 0; i < dst.rows; i++)
 {
  for (int j = 0; j < dst.cols; j++)
  {
   dst.at<Vec3b>(i, j)[0] = dst.at<Vec3b>(i, j)[0] / divideWidth * divideWidth + divideWidth / 2;
   dst.at<Vec3b>(i, j)[1] = dst.at<Vec3b>(i, j)[1] / divideWidth * divideWidth + divideWidth / 2;
   dst.at<Vec3b>(i, j)[2] = dst.at<Vec3b>(i, j)[2] / divideWidth * divideWidth + divideWidth / 2;
  }
 }

上面是彩色图访问方式，下面介绍灰度的访问方式：

        Mat img = imread("D:/Code/Image/classic.jpg", 0); //以灰度图形式读入
	imshow("原图", img);
	
	//1，快，和彩色图一样，只不过像素的个数少了三倍
	for (int i = 0; i < img.rows; i++)
	{
		uchar *p = img.ptr<uchar>(i);
		for (int j = 0; j < img.cols; j++)
		{
			if (p[j] > 150)
				p[j] = 255;
			else
				p[j] = 0;
		}
	}

	//2，简
	/*for (int i = 0; i < img.rows; i++)
	for (int j = 0; j < img.cols; j++)
	{
		if (img.at<uchar>(i, j) > 150)
			img.at<uchar>(i, j) = 255;
		else
			img.at<uchar>(i, j) = 0;
	}*/
	imshow("二值化后", img);