How to do inverse DFT using magnitude and phase of a image in opencv?

Question

I want to show that phase of an image carries more information than that of its magnitude, so I want to exchange the magnitude of two image and then do the inverse DFT. here is the code:

    void main()
{

   Mat I1 = imread("lena.jpg", CV_LOAD_IMAGE_GRAYSCALE);

   Mat I2 = imread("peppers.png", CV_LOAD_IMAGE_GRAYSCALE);

   Mat padded1,padded2;                            

    //expand input image to optimal size
    int m1= getOptimalDFTSize( I1.rows );
    int n1 = getOptimalDFTSize( I1.cols ); 

    int m2= getOptimalDFTSize( I2.rows );
    int n2 = getOptimalDFTSize( I2.cols );

    // on the border add zero values
    copyMakeBorder(I1, padded1, 0, m1 - I1.rows, 0, n1 - I1.cols, BORDER_CONSTANT, Scalar::all(0));
    copyMakeBorder(I2, padded2, 0, m2 - I2.rows, 0, n2 - I2.cols, BORDER_CONSTANT, Scalar::all(0));

    Mat planes1[] = {Mat_<float>(padded1), Mat::zeros(padded1.size(), CV_32F)};
    Mat planes2[] = {Mat_<float>(padded2), Mat::zeros(padded2.size(), CV_32F)};
    Mat complexI, complexII;

    // Add to the expanded another plane with zeros
    merge(planes1, 2, complexI);     
    merge(planes2, 2, complexII);

    dft(complexI, complexI); 
    dft(complexII, complexII);  

    // compute the magnitude and phase then switch to logarithmic scale
    // => magnitude:log(1 + sqrt(Re(DFT(I))^2 + Im(DFT(I))^2)), phase:arctan(Im(DFT(I)),Re(DFT(I)))
    split(complexI, planes1);// planes[0] = Re(DFT(I)), planes[1] = Im(DFT(I))
    Mat ph1, magI1;
    phase(planes1[0], planes1[1], ph1);//ph1 = phase
    magnitude(planes1[0], planes1[1], magI1);// magI1 = magnitude
    magI1 = magI1(Rect(0, 0, magI1.cols & -2, magI1.rows & -2));
    ph1 = ph1(Rect(0, 0, ph1.cols & -2, ph1.rows & -2));

    split(complexII, planes2);// planes[0] = Re(DFT(I)), planes[1] = Im(DFT(I))
    Mat ph2, magI2;
    phase(planes2[0], planes2[1], ph2);//ph2 = phase
    magnitude(planes2[0], planes2[1], magI2);// mag2 = magnitude
    magI2 = magI2(Rect(0, 0, magI2.cols & -2, magI2.rows & -2));
    ph2 = ph2(Rect(0, 0, ph2.cols & -2, ph2.rows & -2));

    planes1[1] = ph1; planes1[0] = magI2;
    planes2[1] = ph2; planes2[0] = magI1;


    dft(complexI,complexI,DFT_INVERSE);
    dft(complexII,complexII,DFT_INVERSE);
    imshow("image", complexI);
    waitKey();
}

I just simply merge magnitude and phase together then do the IDFT, seems totally wrong.

Answer 1

You can't merge the magnitude and phase by using cv::merge() function, instead you should use cv::polarToCart(). Here's my code to do what you want:

using namespace cv;

// Rearrange the quadrants of a Fourier image so that the origin is at
// the image center
void shiftDFT(Mat &fImage )
{
    Mat tmp, q0, q1, q2, q3;

    // first crop the image, if it has an odd number of rows or columns

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

    int cx = fImage.cols / 2;
    int cy = fImage.rows / 2;

    // rearrange the quadrants of Fourier image
    // so that the origin is at the image center

    q0 = fImage(Rect(0, 0, cx, cy));
    q1 = fImage(Rect(cx, 0, cx, cy));
    q2 = fImage(Rect(0, cy, cx, cy));
    q3 = fImage(Rect(cx, cy, cx, cy));

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

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

int main()
{
    // Load an image
    Mat I1 = imread("lena.jpg", CV_LOAD_IMAGE_GRAYSCALE);
    Mat I2 = imread("pepper.jpg", CV_LOAD_IMAGE_GRAYSCALE);

    Mat fI1;
    Mat fI2;
    I1.convertTo(fI1, CV_32F);
    I2.convertTo(fI2, CV_32F);

    //expand input image to optimal size
    int m = getOptimalDFTSize( I1.rows );
    int n = getOptimalDFTSize( I1.cols ); 

    Mat padded1, padded2;

    // on the border add zero values
    copyMakeBorder(fI1, padded1, 0, m - I1.rows, 0, n - I1.cols, BORDER_CONSTANT, Scalar::all(0));
    copyMakeBorder(fI2, padded2, 0, m - I2.rows, 0, n - I2.cols, BORDER_CONSTANT, Scalar::all(0));

    //Perform DFT
    Mat fourierTransform1;
    Mat fourierTransform2;
    Mat planes1[2], planes2[2];

    dft(fI1, fourierTransform1, DFT_SCALE|DFT_COMPLEX_OUTPUT);
    dft(fI2, fourierTransform2, DFT_SCALE|DFT_COMPLEX_OUTPUT);

    shiftDFT(fourierTransform1);
    shiftDFT(fourierTransform2);

    split(fourierTransform1, planes1);// planes[0] = Re(DFT(I)), planes[1] = Im(DFT(I))
    split(fourierTransform2, planes2);// planes[0] = Re(DFT(I)), planes[1] = Im(DFT(I))

    Mat ph1, mag1;
    mag1.zeros(planes1[0].rows, planes1[0].cols, CV_32F);
    ph1.zeros(planes1[0].rows, planes1[0].cols, CV_32F);
    cartToPolar(planes1[0], planes1[1], mag1, ph1);

    Mat ph2, mag2;
    mag2.zeros(planes2[0].rows, planes2[0].cols, CV_32F);
    ph2.zeros(planes2[0].rows, planes2[0].cols, CV_32F);
    cartToPolar(planes2[0], planes2[1], mag2, ph2);

    polarToCart(mag1, ph2, planes1[0], planes1[1]);
    polarToCart(mag2, ph1, planes2[0], planes2[1]);

    merge(planes1, 2, fourierTransform1);
    merge(planes2, 2, fourierTransform2);

    shiftDFT(fourierTransform1);
    shiftDFT(fourierTransform2);

    //Perform IDFT
    Mat inverseTransform1, inverseTransform2;

    dft(fourierTransform1, inverseTransform1, DFT_INVERSE|DFT_REAL_OUTPUT);
    dft(fourierTransform2, inverseTransform2, DFT_INVERSE|DFT_REAL_OUTPUT);

    namedWindow("original image 1");
    imshow("original image 1", I1);
    namedWindow("original image 2");
    imshow("original image 2", I2);
    waitKey(0);

    cv::Mat out1, out2;
    inverseTransform1.convertTo(out1, CV_8U);
    inverseTransform2.convertTo(out2, CV_8U);

    namedWindow("result image 1");
    imshow("result image 1", out1);
    namedWindow("result image 2");
    imshow("result image 2", out2);
    waitKey(0); 
}

Answer 2

I guess from your question that something with your dft is not working. Try the below Code (after adding your split Planes) and see if it works. The images have to be the Exact same Size. If something else is wrong: please show your images and results. Maybe your code is correct and you are just expecting the wrong thing.

Here is the working Example:

// Load an image
Mat I1 = imread("lena.jpg", CV_LOAD_IMAGE_GRAYSCALE);
Mat I2 = imread("peppers.png", CV_LOAD_IMAGE_GRAYSCALE);

Mat fI1;
Mat fI2;
I1.convertTo(fI1, CV_32F);
I2.convertTo(fI2, CV_32F);

//Perform DFT
Mat fourierTransform1;
Mat fourierTransform2;
dft(fI1, fourierTransform1, DFT_SCALE|DFT_COMPLEX_OUTPUT);
dft(fI2, fourierTransform2, DFT_SCALE|DFT_COMPLEX_OUTPUT);

//your split plane and  everything else

//Perform  IDFT
Mat inverseTransform1;
Mat inverseTransform2;
dft(fourierTransform1, inverseTransform1, DFT_INVERSE|DFT_REAL_OUTPUT);
dft(fourierTransform2, inverseTransform2, DFT_INVERSE|DFT_REAL_OUTPUT);  

Mat result1;
Mat result2;
inverseTransform1.convertTo(result1, CV_8U);
inverseTransform2.convertTo(result2, CV_8U);