OpenCV DFT

#include <iostream>
#include <opencv2/opencv.hpp>
using namespace cv;
using namespace std;
int main(int argc, char **argv)
{
    Mat srcImage = imread("/home/cjk/图片/777.png");
    cout << "@@@@@   1   @@@" << endl;
    if (srcImage.empty() )
    {
        std::cerr << "fail to load image " << std::endl;
        return -1;
    }
    //转换为灰度图像
    Mat grayImage;
    cvtColor(srcImage,grayImage,COLOR_BGR2GRAY);
    cout << "@@@@@   2   @@@" << endl;
    //将图像拓展到傅里叶变换的最佳尺寸
    int row = getOptimalDFTSize(grayImage.rows);
    int col = getOptimalDFTSize(grayImage.cols);
    //将扩展后的尺寸设置为0
    Mat padded;
    copyMakeBorder(grayImage,padded,0,row-grayImage.rows,
            0,col-grayImage.cols,BORDER_CONSTANT,Scalar::all(0));
    //傅里叶计算的实部与虚部
    cout << "@@@@@   3   @@@" << endl;
    Mat planes[] = {Mat_<float>(padded),Mat_<float>(padded.size(),CV_32F)};
    Mat complexI;
    merge(planes,2,complexI);
    //进行傅里叶变换
    dft(complexI,complexI);
    //将复数转换为幅值
    cout << "@@@@@   4   @@@" << endl;
    split(complexI,planes);
    magnitude(planes[0],planes[1],planes[0]);
    Mat magnitudeImage = planes[0];
    //尺寸缩放
    magnitudeImage += Scalar::all(1);
    log(magnitudeImage,magnitudeImage);
    cout << "----------------" << endl;
    //剪切和重分布图像
    cout << "magnitudeImage.size() : " << magnitudeImage.size() << endl;
    cout << "magnitudeImage.rows : " << magnitudeImage.rows << endl;
    cout << "magnitudeImage.cols : " << magnitudeImage.cols << endl;
    magnitudeImage  = magnitudeImage(Rect(0,0,magnitudeImage.cols ,magnitudeImage.rows ));
    cout << "----------------" << endl;
    int cx = magnitudeImage.cols / 2;
    int cy = magnitudeImage.rows / 2;
    cout << "cx : " << cx << endl;
    cout << "cy : " << cy << endl;
    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));
    //交换象限 左上和右下
    cout << "@@@@@   6   @@@" << endl;
    Mat temp;
    q0.copyTo(temp);
    q3.copyTo(q0);
    temp.copyTo(q3);
    //右上和左下
    q1.copyTo(temp);
    q2.copyTo(q1);
    temp.copyTo(q2);
    //归一化
    normalize(magnitudeImage,magnitudeImage,0,1,NORM_MINMAX);

    imshow("srcImage",srcImage);
    imshow("freq and Amplitude",magnitudeImage);
    waitKey();
    //cvDestroyAllWindows();
    return 0;
}