#include "program.h"

int main(int argc, char ** argv)
{
    Mat src;
    
    if( argc > 1)
    {
        char* first_file_passed_in = argv[1];
        src = cv::imread( first_file_passed_in, CV_LOAD_IMAGE_GRAYSCALE );
    }
    
    // quit if we didnt read in any data.
    if( src.empty())
        return -1;
    
    //return worksheetone(int argc, char ** argv);
    return worksheettwo(src);
    //return worksheetthree( src);
    //return worksheetfour(src);
    //return worksheetfive( src);
    //return worksheetsix( src);
    //return worksheetseven( src);
    //return worksheeteight( src);
    //return worksheetnine( src);
    //return worksheetten( src);
    //return worksheeteleven( src);
    //return worksheettwelve( src);
    //return worksheetthirteen( src);
    //return worksheetfourteen( src);
}

/**
 * Rearrange the quadrants of a fourier transform
 */
void rearrange( Mat& dftimage)
{
    // rearrange the quadrants of Fourier image  so that the origin is at the image center
    int cx = dftimage.cols/2;
    int cy = dftimage.rows/2;
    
    Mat q0(dftimage, Rect(0, 0, cx, cy));   // Top-Left - Create a ROI per quadrant
    Mat q1(dftimage, Rect(cx, 0, cx, cy));  // Top-Right
    Mat q2(dftimage, Rect(0, cy, cx, cy));  // Bottom-Left
    Mat q3(dftimage, 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);
}

/**
 * Rotate an image
 */
void rotate(cv::Mat& src, double angle, cv::Mat& dst)
{
    cv::Point2f pt(src.cols/2., src.rows/2.);
    cv::Mat r = cv::getRotationMatrix2D(pt, angle, 1.0);
    
    cv::warpAffine(src, dst, r, cv::Size(src.cols, src.rows));
}

// here we produce a magnitude image so that we can view our fourier transform.
// i.e. we want a new image whose values are sqrt( X^2+ Y^2) of our complex image X+iY.
Mat computeMagnitudeImage(Mat& complexImage)
{
    Mat planes[] = {Mat::zeros(complexImage.size(), CV_32F), Mat::zeros(complexImage.size(), CV_32F)};
    
    // split the complex image back into its Re and Imaginary parts.
    // planes[0] = Re(DFT(I)), planes[1] = Im(DFT(I))
    split(complexImage, planes);
    
    // Now, we are going to compute the magnitude of our complex image.
    // i.e. we want a new image whose values are sqrt( X^2+ Y^2) of our complex image X+iY.
    Mat magnitudeImage;
    // luckily for us, there is an easy way to compute this.
    magnitude(planes[0], planes[1], magnitudeImage);
    
    // compute the magnitude and switch to logarithmic scale
    // => log(1 + sqrt(Re(DFT(I))^2 + Im(DFT(I))^2))
    magnitudeImage += Scalar::all(1);                    // switch to logarithmic scale
    log(magnitudeImage, magnitudeImage);
    
    // crop the spectrum, if it has an odd number of rows or columns
    magnitudeImage = magnitudeImage(Rect(0, 0, magnitudeImage.cols & -2, magnitudeImage.rows & -2));
    
    // Transform the matrix with float values into a
    // viewable image form (float between values 0 and 1).
    normalize(magnitudeImage, magnitudeImage, 0, 1, CV_MINMAX);
    
    return magnitudeImage;
}

Mat embedInComplexImage(Mat& realImage)
{
    // Now, because of the way the DFT works, we are going to need to pad our image,
    // i.e. we are going to have to add some empty space around the image so that it has an
    // 'optimal' size for the DFT.
    Mat padded;
    
    //we now compute the optimal image size for our matrix.
    int m = getOptimalDFTSize( realImage.rows );
    int n = getOptimalDFTSize( realImage.cols );
    
    // add some padding to our image, so that it becomes an m x n matrix,
    // on the border add zero values
    copyMakeBorder(realImage, padded, 0, m - realImage.rows, 0, n - realImage.cols, BORDER_CONSTANT, Scalar::all(0));
    
    // This is the COMPLEX version of our image.
    Mat complexImage;
    // we are going to set the values of this image to be X + 0i, where X are the
    // original pixel values in our image. I.e. the real part is our original image.
    
    // create an array of images, the first one will be the REAL part of our DFT image,
    // and the second one will be the complex part.
    Mat planes[] = {Mat_<float>(padded), Mat::zeros(padded.size(), CV_32F)};
    
    // add both of these planes together to make our complex image. X+0i.
    merge(planes, 2, complexImage);         // Add to the expanded another plane with zeros
    
    return complexImage;
    
}