opencv去除图像的正弦噪声，c++代码

以下是使用opencv去除图像的正弦噪声的C代码示例：

#include <stdio.h>
#include <opencv2/opencv.hpp>

using namespace cv;

int main(int argc, char** argv )
{
    if ( argc != 2 )
    {
        printf("usage: remove_noise <Image_Path>\n");
        return -1;
    }

    Mat image, gray, dst;
    image = imread( argv[1], 1 );

    if ( !image.data )
    {
        printf("No image data \n");
        return -1;
    }

    cvtColor(image, gray, COLOR_BGR2GRAY);

    // Apply FFT to the image
    Mat fft_image;
    dft(gray, fft_image, DFT_COMPLEX_OUTPUT);

    // Create a filter to remove the noise
    Mat filter(gray.size(), CV_32FC2, Scalar(0));
    const int radius = 30;
    const float strength = 10.0f;
    Point center(gray.cols / 2, gray.rows / 2);
    for (int i = 0; i < gray.rows; i++)
    {
        for (int j = 0; j < gray.cols; j++)
        {
            float distance = norm(Point(j, i) - center);
            if (distance <= radius)
            {
                filter.at<Vec2f>(i, j)[0] = strength;
                filter.at<Vec2f>(i, j)[1] = strength;
            }
        }
    }

    // Apply the filter to the image in frequency domain
    Mat filtered_image;
    mulSpectrums(fft_image, filter, filtered_image, 0);

    // Apply inverse FFT to get the filtered image
    idft(filtered_image, dst, DFT_SCALE | DFT_REAL_OUTPUT);

    // Convert the image back to uint8 format
    dst.convertTo(dst, CV_8U);

    namedWindow("Original Image", WINDOW_NORMAL);
    namedWindow("Filtered Image", WINDOW_NORMAL);
    imshow("Original Image", image);
    imshow("Filtered Image", dst);
    waitKey(0);

    return 0;
}

这个代码示例首先读取图像，并将其转换为灰度图像。然后，它使用FFT（快速傅里叶变换）对图像进行处理，以便滤除正弦噪声。它创建了一个滤波器来滤除噪声，并将其应用于频域中的图像。最后，它使用逆FFT将滤波器应用于图像，并将其转换回uint8格式以进行显示。