opencv/samples/cpp/dft.cpp
Roman Donchenko 2c4bbb313c Merge commit '43aec5ad' into merge-2.4
Conflicts:
	cmake/OpenCVConfig.cmake
	cmake/OpenCVLegacyOptions.cmake
	modules/contrib/src/retina.cpp
	modules/gpu/doc/camera_calibration_and_3d_reconstruction.rst
	modules/gpu/doc/video.rst
	modules/gpu/src/speckle_filtering.cpp
	modules/python/src2/cv2.cv.hpp
	modules/python/test/test2.py
	samples/python/watershed.py
2013-08-27 13:26:44 +04:00

83 lines
2.1 KiB
C++

#include "opencv2/core.hpp"
#include "opencv2/core/utility.hpp"
#include "opencv2/imgproc.hpp"
#include "opencv2/highgui.hpp"
#include <stdio.h>
using namespace cv;
using namespace std;
static void help()
{
printf("\nThis program demonstrated the use of the discrete Fourier transform (dft)\n"
"The dft of an image is taken and it's power spectrum is displayed.\n"
"Usage:\n"
"./dft [image_name -- default lena.jpg]\n");
}
const char* keys =
{
"{@image|lena.jpg|input image file}"
};
int main(int argc, const char ** argv)
{
help();
CommandLineParser parser(argc, argv, keys);
string filename = parser.get<string>(0);
Mat img = imread(filename.c_str(), IMREAD_GRAYSCALE);
if( img.empty() )
{
help();
printf("Cannot read image file: %s\n", filename.c_str());
return -1;
}
int M = getOptimalDFTSize( img.rows );
int N = getOptimalDFTSize( img.cols );
Mat padded;
copyMakeBorder(img, padded, 0, M - img.rows, 0, N - img.cols, BORDER_CONSTANT, Scalar::all(0));
Mat planes[] = {Mat_<float>(padded), Mat::zeros(padded.size(), CV_32F)};
Mat complexImg;
merge(planes, 2, complexImg);
dft(complexImg, complexImg);
// compute log(1 + sqrt(Re(DFT(img))**2 + Im(DFT(img))**2))
split(complexImg, planes);
magnitude(planes[0], planes[1], planes[0]);
Mat mag = planes[0];
mag += Scalar::all(1);
log(mag, mag);
// crop the spectrum, if it has an odd number of rows or columns
mag = mag(Rect(0, 0, mag.cols & -2, mag.rows & -2));
int cx = mag.cols/2;
int cy = mag.rows/2;
// rearrange the quadrants of Fourier image
// so that the origin is at the image center
Mat tmp;
Mat q0(mag, Rect(0, 0, cx, cy));
Mat q1(mag, Rect(cx, 0, cx, cy));
Mat q2(mag, Rect(0, cy, cx, cy));
Mat q3(mag, Rect(cx, cy, cx, cy));
q0.copyTo(tmp);
q3.copyTo(q0);
tmp.copyTo(q3);
q1.copyTo(tmp);
q2.copyTo(q1);
tmp.copyTo(q2);
normalize(mag, mag, 0, 1, NORM_MINMAX);
imshow("spectrum magnitude", mag);
waitKey();
return 0;
}