c++ - 如何在opencv中使用图像的幅度和相位进行逆DFT？

Question

我想证明图像的相位比其幅值包含更多信息，所以我想交换两个图像的幅值，然后进行逆向 DFT。这是代码:

    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();
}

我只是简单地将幅度和相位合并在一起然后进行 IDFT，看起来完全错误。

Answer 1

我从你的问题中猜想你的 dft 有什么不工作。试试下面的代码(在添加你的分割平面之后)看看它是否有效。图片的尺寸必须完全相同。如果有其他问题:请显示您的图像和结果。也许您的代码是正确的，而您只是期待错误的事情。

这是工作示例:

// 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);