opencv的強大之處，從這裡開始，越來越能和訊號處理接軌了，贊一個。

程式碼:

#include <opencv2/core/core.hpp>
#include <opencv2/imgproc/imgproc.hpp>
#include <opencv2/highgui/highgui.hpp>
#include <iostream>

using namespace std;
using namespace cv;

// "/mnt/hgfs/code_for_Linux/code_opencv/test1/pic/"
int main()
{
    Mat srcImage = imread("/mnt/hgfs/code_for_Linux/code_opencv/test1/pic/3.jpg", 0);

    if (!srcImage.data) {
        return -1;
    }

    imshow("[灰度圖]", srcImage);

    int m = getOptimalDFTSize(srcImage.rows);
    int n = getOptimalDFTSize(srcImage.cols);

    Mat padded;
    copyMakeBorder(srcImage, padded, 0, m - srcImage.rows, 0, n - srcImage.cols,
                   BORDER_CONSTANT, Scalar::all(0));

    Mat planes[] = {Mat_<float>(padded), Mat::zeros(padded.size(), CV_32F)};
    Mat complexI;
    merge(planes, 2, complexI);

    dft(complexI, complexI);

    split(complexI, planes);
    magnitude(planes[0], planes[1], planes[0]);
    Mat magnitudeImage = planes[0];

    magnitudeImage += Scalar::all(1);
    log(magnitudeImage, magnitudeImage);

    magnitudeImage = magnitudeImage(Rect(0,
                                         0,
                                         magnitudeImage.cols & - 2,
                                         magnitudeImage.rows & - 2));

    int cx = magnitudeImage.cols/2;
    int cy = magnitudeImage.rows/2;
    Mat q0(magnitudeImage, Rect(0, 0, cx, cy));
    Mat q1(magnitudeImage, Rect(cx, 0, cx, cy));
    Mat q2(magnitudeImage, Rect(0, cy, cx, cy));
    Mat q3(magnitudeImage, Rect(cx, cy, cx, cy));

    Mat tmp;
    q0.copyTo(tmp);
    q3.copyTo(q0);
    tmp.copyTo(q3);

    q1.copyTo(tmp);
    q2.copyTo(q1);
    tmp.copyTo(q2);

    normalize(magnitudeImage, magnitudeImage, 0, 1, NORM_MINMAX);

    imshow("頻譜幅值", magnitudeImage);
    waitKey(0);
    return 0;
}




 

效果如下：

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