利用OpenCV给彩色图像添加椒盐噪声的方法

#include <opencv2\opencv.hpp>
#include <iostream>

using namespace cv;
using namespace std;

//-----------------------------------椒盐噪声函数----------------------------------------------
void saltAndPepper(cv::Mat image, int n)
{
	for (int k = 0; k < n / 2; k++)
	{
		// 随机确定图像中添加椒盐噪声的位置
		int i, j;
		i = std::rand() % image.cols;       // 取余数运算，保证在图像的列数内 
		j = std::rand() % image.rows;       // 取余数运算，保证在图像的行数内 
		int write_black = std::rand() % 2;  // 判定为白色噪声还是黑色噪声的变量
		// 添加白色噪声
		if (write_black == 0)               
		{
			image.at<cv::Vec3b>(j, i)[0] = 255; //cv::Vec3b为opencv定义的一个3个值的向量类型  
			image.at<cv::Vec3b>(j, i)[1] = 255; //[]指定通道，B:0，G:1，R:2  
			image.at<cv::Vec3b>(j, i)[2] = 255;

		}
		// 添加黑色噪声
		else  
		{
			image.at<cv::Vec3b>(j, i)[0] = 0; //cv::Vec3b为opencv定义的一个3个值的向量类型  
			image.at<cv::Vec3b>(j, i)[1] = 0; //[]指定通道，B:0，G:1，R:2  
			image.at<cv::Vec3b>(j, i)[2] = 0;
		}
	}

}


int main()
{
	Mat lena = imread("qq.jpg");

	if (lena.empty())
	{
		cout << "请确认图像文件名称是否正确" << endl;
		return -1;
	}
	imshow("原图", lena);
	saltAndPepper(lena, 10000);       // 彩色图像添加椒盐噪声
	imshow("添加噪声", lena);

	waitKey(0);

	return 0;
}

import numpy as np
import cv2


def salt_pepper_noise(image, prob):
    """
    添加椒盐噪声
    :param image: 输入图像
    :param prob: 噪声比
    :return: 带有椒盐噪声的图像
    """
    salt = np.zeros(image.shape, np.uint8)
    thres = 1 - prob
    for i in range(image.shape[0]):
        for j in range(image.shape[1]):
            rdn = np.random.rand()
            if rdn < prob:
                salt[i][j] = 0
            elif rdn > thres:
                salt[i][j] = 255
            else:
                salt[i][j] = image[i][j]
    return salt


src = cv2.imread('qq.jpg')
cv2.namedWindow('input_image', cv2.WINDOW_AUTOSIZE)
cv2.imshow('input_image', src)
tar = salt_pepper_noise(src, 0.01)
cv2.imshow('noise', tar)
cv2.waitKey(0)
cv2.destroyAllWindows()