opencv给图像添加椒盐噪声和高斯噪声

U1和U2可以是随机值，经过上式产生的随机变量Z0，Z1满足标准高斯分布

实现代码如下：

#include
#include
#include
#include

using namespace std;
using namespace cv;
//给图像添加椒盐噪声
Mat addSaltNoise(Mat src, int n)
{
	Mat result = src.clone();
	for (int k = 0; k < n; k++)
	{
		//随机选取行列值
		int i = rand() % result.cols;
		int j = rand() % result.rows;
		if (result.channels() == 1)
		{
			result.at(j, i) = 255;
		}
		else
		{
			result.at(j, i)[0] = 255;
			result.at(j, i)[1] = 255;
			result.at(j, i)[2] = 255;
		}

	}
	return result;
}

//给图像添加高斯噪声
double generateGaussianNoise(double mu, double sigma)
{
	//定义最小值
	double epsilon = numeric_limits::min();
	double z0=0, z1=0;
	bool flag = false;
	flag = !flag;
	if (!flag)
		return z1*sigma + mu;
	double u1, u2;
	do
	{
		u1 = rand()*(1.0 / RAND_MAX);
		u2 = rand()*(1.0/RAND_MAX);
	} while (u1 <= epsilon);
	z0 = sqrt(-2.0*log(u1))*cos(2*CV_PI*u2);
	z1 = sqrt(-2.0*log(u1))*sin(2 * CV_PI*u2);
	return z0*sigma + mu;
}

Mat addGaussianNoise(Mat& src)
{
	Mat result = src.clone();
	int channels = result.channels();
	int nRows = result.rows;
	int nCols = result.cols*channels;
	if (result.isContinuous())
	{
		nCols = nCols*nRows;
		nRows = 1;
	}
	for (int i = 0; i < nRows; i++)
	{
		for (int j = 0; j < nCols; j++)
		{
			int val = result.ptr(i)[j] + generateGaussianNoise(2, 0.8)*32;
			if (val < 0)
				val = 0;
			if (val > 255)
				val = 255;
			result.ptr(i)[j] = (uchar)val;
		}
	}
	return result;
}
int main()
{
	//imread中0表示灰度返回，1表示原图返回
	Mat src = imread("E:\\研究生\\学习材料\\学习书籍\\OpenCV图像处理编程实例-源码-20160801\\《OpenCV图像处理编程实例-源码-20160801\\images\\flower3.jpg",0);
	if (!src.data)
		return -1;
	Mat dst;
	//dst=addSaltNoise(src, 100);
	dst = addGaussianNoise(src);
	//imshow("SaltNoise",dst);
	imshow("GaussianNoise", dst);
	waitKey(0);
	return(0);
}

结果如图：