C++ opencv Discrete Fourier

#include <opencv2/core/core.hpp>
#include <opencv2/highgui/highgui.hpp>
#include <opencv2/imgproc/imgproc.hpp>
#include <iostream>
#include <thread>
#include <Windows.h>
using namespace cv;
using namespace std;

int main(int argc, char ** argv)
{
//const char* filename = argc >= 2 ? argv[1] : "lena.jpg";

//Mat I = imread("C:\\Users\\Public\\Pictures\\Sample Pictures\\Lighthouse.jpg", CV_LOAD_IMAGE_GRAYSCALE);
//if (I.empty())
// return -1;

//Mat padded;                            //expand input image to optimal size
//int m = getOptimalDFTSize(I.rows);
//int n = getOptimalDFTSize(I.cols); // on the border add zero values
//copyMakeBorder(I, padded, 0, m - I.rows, 0, n - I.cols, BORDER_CONSTANT, Scalar::all(0));

//Mat planes[] = { Mat_<float>(padded), Mat::zeros(padded.size(), CV_32F) };
//Mat complexI;
//merge(planes, 2, complexI);         // Add to the expanded another plane with zeros

//dft(complexI, complexI);            // this way the result may fit in the source matrix

// // compute the magnitude and switch to logarithmic scale
// // => log(1 + sqrt(Re(DFT(I))^2 + Im(DFT(I))^2))
//split(complexI, planes);                   // planes[0] = Re(DFT(I), planes[1] = Im(DFT(I))
//magnitude(planes[0], planes[1], planes[0]);// planes[0] = magnitude
//Mat magI = planes[0];

//magI += Scalar::all(1);                    // switch to logarithmic scale
//log(magI, magI);

//// crop the spectrum, if it has an odd number of rows or columns
//magI = magI(Rect(0, 0, magI.cols & -2, magI.rows & -2));

//// rearrange the quadrants of Fourier image  so that the origin is at the image center
//int cx = magI.cols / 2;
//int cy = magI.rows / 2;

//Mat q0(magI, Rect(0, 0, cx, cy));   // Top-Left - Create a ROI per quadrant
//Mat q1(magI, Rect(cx, 0, cx, cy));  // Top-Right
//Mat q2(magI, Rect(0, cy, cx, cy));  // Bottom-Left
//Mat q3(magI, Rect(cx, cy, cx, cy)); // Bottom-Right

//Mat tmp;                           // swap quadrants (Top-Left with Bottom-Right)
//q0.copyTo(tmp);
//q3.copyTo(q0);
//tmp.copyTo(q3);

//q1.copyTo(tmp);                    // swap quadrant (Top-Right with Bottom-Left)
//q2.copyTo(q1);
//tmp.copyTo(q2);

//normalize(magI, magI, 0, 1, CV_MINMAX); // Transform the matrix with float values into a
// // viewable image form (float between values 0 and 1).

//Mat tmp2(magI.rows, magI.cols, magI.type());
//circle(tmp2, Point(magI.cols/2, magI.rows/2), 500, Scalar(1),-1);
//Mat tmp3(magI.rows, magI.cols, magI.type());
//tmp3 = min(tmp2 , magI );
//Mat tmp4(magI.rows, magI.cols, magI.type());

//cv::Mat inverseTransform,out2;
//cv::dft(I, inverseTransform,  cv::DFT_REAL_OUTPUT);
//cv::dft(inverseTransform, out2, cv::DFT_INVERSE | cv::DFT_REAL_OUTPUT);


//imshow("Input Image", I);    // Show the result
//imshow("spectrum magnitude", complexI);
//imshow("sxx", out2);

//imshow("sxx2", inverseTransform);
waitKey();


////////////////////////////

Mat I = imread("D:\\111.jpg", CV_LOAD_IMAGE_GRAYSCALE);
if (I.empty())
return -1;

Mat padded;                            //expand input image to optimal size
int m = getOptimalDFTSize(I.rows);
int n = getOptimalDFTSize(I.cols); // on the border add zero values
copyMakeBorder(I, padded, 0, m - I.rows, 0, n - I.cols, BORDER_CONSTANT, Scalar::all(0));

Mat planes[] = { Mat_<float>(padded), Mat::zeros(padded.size(), CV_32F) };
Mat complexI;
merge(planes, 2, complexI);         // Add to the expanded another plane with zeros

dft(complexI, complexI);            // this way the result may fit in the source matrix

// compute the magnitude and switch to logarithmic scale
// => log(1 + sqrt(Re(DFT(I))^2 + Im(DFT(I))^2))
split(complexI, planes);                   // planes[0] = Re(DFT(I), planes[1] = Im(DFT(I))

magnitude(planes[0], planes[1], planes[0]);// planes[0] = magnitude
Mat magI = planes[0];

magI += Scalar::all(1);                    // switch to logarithmic scale
log(magI, magI);

// crop the spectrum, if it has an odd number of rows or columns
magI = magI(Rect(0, 0, magI.cols & -2, magI.rows & -2));

// rearrange the quadrants of Fourier image  so that the origin is at the image center
int cx = magI.cols / 2;
int cy = magI.rows / 2;

Mat q0(magI, Rect(0, 0, cx, cy));   // Top-Left - Create a ROI per quadrant
Mat q1(magI, Rect(cx, 0, cx, cy));  // Top-Right
Mat q2(magI, Rect(0, cy, cx, cy));  // Bottom-Left
Mat q3(magI, Rect(cx, cy, cx, cy)); // Bottom-Right

Mat tmp;                           // swap quadrants (Top-Left with Bottom-Right)
q0.copyTo(tmp);
q3.copyTo(q0);
tmp.copyTo(q3);

q1.copyTo(tmp);                    // swap quadrant (Top-Right with Bottom-Left)
q2.copyTo(q1);
tmp.copyTo(q2);

Mat phaseVals(640, 480, CV_8UC3);
normalize(magI, magI, 0, 1, CV_MINMAX); // Transform the matrix with float values into a
normalize(phaseVals, phaseVals, 0, 1, CV_MINMAX);
// viewable image form (float between values 0 and 1).

imshow("Input Image", I);    // Show the result
imshow("Spectrum Magnitude", magI);
waitKey();

//calculating the idft
cv::Mat inverseTransform;
cv::dft(complexI, inverseTransform, cv::DFT_INVERSE | cv::DFT_REAL_OUTPUT);
normalize(inverseTransform, inverseTransform, 0, 1, CV_MINMAX);
imshow("Reconstructed", inverseTransform);
waitKey();

return 0;
}