發現Mat類中的at方法對於獲取圖像矩陣某點的RGB值或者改變某點的值很方便，對於單通道的圖像，則可以使用：

<span style="font-size:18px;">image.at<uchar>(i, j)</span>

<span style="font-size:18px;">image.at<Vec3b>(i, j)[0]
image.at<Vec3b>(i, j)[1]
image.at<Vec3b>(i, j)[2]</span>

<span style="font-size:18px;">#include<opencv2\opencv.hpp>
using namespace cv;
using namespace std;

void salt_noise(Mat image, int time)
{
	for (int k = 0; k < time; k++)//time is the number of the noise you add
	{
		int i = rand() % image.rows;
		int j = rand() % image.cols;
		if (image.channels() == 1)//single channel
		{
			image.at<uchar>(i, j) = rand() % 255;
		}
		else if (image.channels() == 3)//RGB channel
		{
			image.at<Vec3b>(i, j)[0] = rand() % 255;
			image.at<Vec3b>(i, j)[1] = rand() % 255;
			image.at<Vec3b>(i, j)[2] = rand() % 255;
		}
	}
}

int main(void)
{
	Mat image = imread("..\\lena.bmp", 0);
	if (image.empty())
	{
		cout << "load image error" << endl;
		return -1;
	}
	salt_noise(image, 3000);
	namedWindow("image", 1);
	imshow("image", image);

	waitKey();
	return 0;
}</span>

不過貌似用at取值或改變值來做比較耗時，當然我們還可以使用Mat的模板子類Mat_<T>,，對於單通道的具體使用：

<span style="font-size:18px;">Mat_<uchar> img = image;
img(i, j) = rand() % 255;</span>

<span style="font-size:18px;">Mat_<Vec3b> img = image;
img(i, j)[0] = rand() % 255;
img(i, j)[1] = rand() % 255;
mg(i, j)[2] = rand() % 255;</span>

還可以用指針的方法遍歷每一像素：（耗時較小）

<span style="font-size:18px;">void colorReduce(Mat image, int div = 64)
{
	int nrow = image.rows;
	int ncol = image.cols*image.channels();
	for (int i = 0; i < nrow; i++)
	{
		uchar* data = image.ptr<uchar>(i);//get the address of row i;
		for (int j = 0; j < ncol; j++)
		{
			data[i] = (data[i] / div)*div ;
		}
	}
}</span>