// =================
// || Worksheet 7
// || In this example, we are going be performing low/high pass filters.
// =================

#include "program.h"

using namespace std;
using namespace cv;



// In this worksheet, we will be performing DFT's and Inverse DFT's
int worksheetseven(Mat& src)
{
    
    // embed our image into a complex image
    Mat complexImage = embedInComplexImage(src);
    // and now take the DFT.
    dft(complexImage, complexImage);
    
    // Now, right after we have performed the DFT. we are going to modify the spectrum image.
    // all of the low frequency data is stored need the corners of the image.
    //we are going to do a quick swap of the quadrants of our image, so that it is easier to edit.
    rearrange(complexImage);
    
    // let us set all of the low frequency data to zero!
    Point centerPoint(complexImage.cols/2,complexImage.rows/2 );
    
    // A LOW PASS FILTER:
    // lets draw a black filled-in cirlce at the center point of the image, of radius 5 pixels.
    // Scalar(0,0,0) means black
    float low_pass_circle_radius = 100;
    circle(complexImage, centerPoint, low_pass_circle_radius, Scalar( 0, 0, 0 ),CV_FILLED);

    // A HIGH PASS FILTER:
    // now, we are going to make black everything that is OUTSIDE a circle.
    // first, loop over all pixels that are in the complexImage.
    float high_pass_circle_radius = 50.0;
    
    // so, we are going to loop over all the rows
    for(int row = 0; row < complexImage.rows ; row++)
    {
        // and loop over each column
        for( int col = 0; col < complexImage.cols; col++)
        {
            // if that pixel is greater than a certain distance from the center, then set it to black.
            Point pt(col, row);
            
            float distance_to_center =
            sqrt( (col - complexImage.cols/2)*(col - complexImage.cols/2) +
                 (row - complexImage.rows/2)*(row - complexImage.rows/2) ) ;
            
            if( distance_to_center > high_pass_circle_radius )
            {
                //complexImage.at<complex<float>>(pt) = complex<float>(0.0,0.0);
            }
            
        } // end of the 'column' for loop
    } // end of the 'row' for loop
    
    
    
    // make sure we rearrange it back.
    rearrange(complexImage);
    
    Mat magnitudeImage = computeMagnitudeImage(complexImage);
   
    rearrange(magnitudeImage);
    
    // Show the result
    imshow("Input Image"       , src   );
    imshow("Modified Spectrum Magnitude", magnitudeImage);
    waitKey();
    
    //calculating the IDFT
    cv::Mat invtransformedImage;
    
    // perform the inverse transform of our complex image.
    cv::dft(complexImage, invtransformedImage, cv::DFT_INVERSE | cv::DFT_REAL_OUTPUT);
    
    /// just normalize our image to be safe.
    normalize(invtransformedImage, invtransformedImage, 0, 1, CV_MINMAX);
    
    imshow("Reconstructed", invtransformedImage);
    waitKey();
    
    return 0;
}