void applyFilter(Mat_<float> src, Mat_<float> output)
{
int wxOrig = src.cols;
int wyOrig = src.rows;
int m = cv::getOptimalDFTSize(2*wyOrig);
int n = cv::getOptimalDFTSize(2*wxOrig);
copyMakeBorder(src, src, 0, m - wyOrig, 0, n - wxOrig, cv::BORDER_CONSTANT, cv::Scalar::all(0));
const int wx = src.cols, wy = src.rows;
const int cx = wx/2, cy = wy/2;
std::cout << wxOrig << " " << wyOrig << std::endl;
std::cout << wx << " " << wy << std::endl;
std::cout << cx << " " << cy << std::endl;
cv::Mat_<float> imgs[] = {src.clone(), cv::Mat_<float>::zeros(wy, wx)};
cv::Mat_<cv::Vec2f> img_dft;
cv::merge(imgs, 2, img_dft);
cv::dft(img_dft, img_dft);
dftshift(img_dft);
cout << "helo " << endl;
cv::Mat hpf = BHPF(3000, 4, wy, wx, cx, cy);
cv::mulSpectrums(hpf, img_dft, img_dft, cv::DFT_ROWS);
dftshift(img_dft);
cv::idft(img_dft, img_dft); //the result is a 2 channel image
split(img_dft, imgs);
normalize(imgs[0], output, 0, 1, CV_MINMAX);
cv::Mat_<float> croppedOutput(output,cv::Rect(0,0,wxOrig,wyOrig));
output = croppedOutput;
namedWindow("High-pass filtered input",WINDOW_NORMAL);
namedWindow("Input",WINDOW_NORMAL);
cv::imshow("Input", src);
cv::imshow("High-pass filtered input", croppedOutput);
imwrite("/home/student/ROVI/VisMand1/build-vis_man_1-Desktop-Debug/output/out.jpg",croppedOutput);
cout << "lol" << endl;
cv::waitKey(0);
}
int main()
{
// A gray image
cv::Mat_<float> img = cv::imread("Image4_1.png", CV_LOAD_IMAGE_GRAYSCALE);
// Load image
// cv::Mat_<float> img = cv::imread(argv[1], cv::IMREAD_GRAYSCALE);
// Get original size
int wxOrig = img.cols;
int wyOrig = img.rows;
int m = cv::getOptimalDFTSize( 2*wyOrig );
int n = cv::getOptimalDFTSize( 2*wxOrig );
copyMakeBorder(img, img, 0, m - wyOrig, 0, n - wxOrig, cv::BORDER_CONSTANT, cv::Scalar::all(0));
// Get padded image size
const int wx = img.cols, wy = img.rows;
const int cx = wx/2, cy = wy/2;
std::cout << wxOrig << " " << wyOrig << std::endl;
std::cout << wx << " " << wy << std::endl;
std::cout << cx << " " << cy << std::endl;
// Compute DFT of image
cv::Mat_<float> imgs[] = {img.clone(), cv::Mat_<float>::zeros(wy, wx)};
cv::Mat_<cv::Vec2f> img_dft;
cv::merge(imgs, 2, img_dft);
cv::dft(img_dft, img_dft);
// Shift to center
dftshift(img_dft);
// Used for visualization only
cv::Mat_<float> magnitude, phase;
cv::split(img_dft, imgs);
cv::cartToPolar(imgs[0], imgs[1], magnitude, phase);
magnitude = magnitude + 1.0f;
cv::log(magnitude, magnitude);
cv::normalize(magnitude, magnitude, 0, 1, CV_MINMAX);
cv::imwrite("img_dft.png", magnitude * 255);
// cv::imshow("img_dft", magnitude);
// Create a Butterworth low-pass filter of order n and diameter d0 in the frequency domain
cv::Mat lpf = BLPF(100, 2, wy, wx, cx, cy);
cv::Mat bsf = BBSF(2, wy, wx, cx, cy);
cv::Mat nf = BNF(2, wy, wx, cx, cy);
// Multiply and shift back
cv::mulSpectrums(nf, img_dft, img_dft, cv::DFT_ROWS);
dftshift(img_dft);
//Display high pass filter
cv::Mat realImg[2];
cv::split(nf,realImg);
cv::Mat realNF = realImg[0];
cv::normalize(realNF, realNF, 0.0, 1.0, CV_MINMAX);
// namedWindow("", cv::WINDOW_NORMAL);
cv::imwrite("NF.png", realNF);
//----- Compute IDFT of HPF filtered image
//you can do this
//cv::idft(img_dft, img_dft); //the result is a 2 channel image
//Mat output;
// therefore you split it and get the real one
//split(img_dft, imgs);
//normalize(imgs[0], output, 0, 1, CV_MINMAX);
//or you can do like this, then you dont need to split
cv::Mat_<float> output;
cv::dft(img_dft, output, cv::DFT_INVERSE| cv::DFT_REAL_OUTPUT);
cv::Mat_<float> croppedOutput(output,cv::Rect(0,0,wxOrig,wyOrig));
cv::normalize(output, output, 0, 1, CV_MINMAX);
cv::normalize(img, img, 0.0, 1.0, CV_MINMAX);
// namedWindow("", cv::WINDOW_NORMAL);
// cv::imshow("Input", img);
cv::imwrite("out.png", croppedOutput * 255);
// namedWindow("", cv::WINDOW_NORMAL);
// cv::imshow("High-pass filtered input", croppedOutput);
cv::waitKey();
return 0;
return 0;
}
