opencv c++给视频加上椒盐噪声和高斯噪声

给视频加上椒盐噪声和高斯噪声可以分为以下几个步骤：

1. 读入视频文件

cv::VideoCapture cap("path/to/video/file");

2. 循环遍历视频的每一帧，并对每一帧添加噪声

while (cap.isOpened()) {
    cv::Mat frame;
    cap >> frame;
    
    // 添加椒盐噪声
    cv::Mat salt_pepper_noise = addSaltPepperNoise(frame, 0.01); // 噪声密度为0.01
    
    // 添加高斯噪声
    cv::Mat gaussian_noise = addGaussianNoise(frame, 0, 20); // 均值为0，标准差为20
    
    // 显示加噪声后的图像
    cv::imshow("Salt and Pepper Noise", salt_pepper_noise);
    cv::imshow("Gaussian Noise", gaussian_noise);
    
    // 等待键盘输入，按下ESC键退出循环
    if (cv::waitKey(1) == 27) {
        break;
    }
}

3. 编写函数实现添加噪声的功能

添加椒盐噪声的函数：

cv::Mat addSaltPepperNoise(const cv::Mat& image, float density) {
    cv::Mat result = image.clone();
    
    int height = result.rows;
    int width = result.cols;
    int channels = result.channels();
    
    int num_salt_pixels = static_cast<int>(density * height * width);
    int num_pepper_pixels = static_cast<int>(density * height * width);
    
    for (int i = 0; i < num_salt_pixels; i++) {
        int row = std::rand() % height;
        int col = std::rand() % width;
        
        if (channels == 1) { // 灰度图像
            result.at<uchar>(row, col) = 255;
        } else if (channels == 3) { // 彩色图像
            result.at<cv::Vec3b>(row, col)[0] = 255;
            result.at<cv::Vec3b>(row, col)[1] = 255;
            result.at<cv::Vec3b>(row, col)[2] = 255;
        }
    }
    
    for (int i = 0; i < num_pepper_pixels; i++) {
        int row = std::rand() % height;
        int col = std::rand() % width;
        
        if (channels == 1) { // 灰度图像
            result.at<uchar>(row, col) = 0;
        } else if (channels == 3) { // 彩色图像
            result.at<cv::Vec3b>(row, col)[0] = 0;
            result.at<cv::Vec3b>(row, col)[1] = 0;
            result.at<cv::Vec3b>(row, col)[2] = 0;
        }
    }
    
    return result;
}

添加高斯噪声的函数：

cv::Mat addGaussianNoise(const cv::Mat& image, double mean, double stddev) {
    cv::Mat result = image.clone();
    
    int height = result.rows;
    int width = result.cols;
    int channels = result.channels();
    
    cv::Mat noise(height, width, CV_64FC(channels));
    cv::randn(noise, mean, stddev);
    
    cv::Mat noisy_image;
    result.convertTo(noisy_image, CV_64FC(channels));
    noisy_image += noise;
    noisy_image.convertTo(result, image.type());
    
    return result;
}

注意：在使用 `std::rand()` 生成随机数之前，需要调用 `std::srand()` ，并传入一个种子值。例如：

std::srand(static_cast<unsigned int>(std::time(nullptr)));