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Open Source Computer Vision Library
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75 lines
1.9 KiB
75 lines
1.9 KiB
#include <opencv2/core/core.hpp> |
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#include <opencv2/imgproc/imgproc.hpp> |
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#include <opencv2/highgui/highgui.hpp> |
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#include <iostream> |
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using namespace cv; |
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using namespace std; |
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void help() |
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{ |
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cout << "\nThis program demonstrated the use of the discrete Fourier transform (dft)\n" |
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"The dft of an image is taken and it's power spectrum is displayed.\n" |
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"Call:\n" |
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"./dft [image_name -- default lena.jpg]\n" << endl; |
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} |
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int main(int argc, char ** argv) |
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{ |
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const char* filename = argc >=2 ? argv[1] : "lena.jpg"; |
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Mat img = imread(filename, CV_LOAD_IMAGE_GRAYSCALE); |
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if( img.empty() ) |
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{ |
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help(); |
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return -1; |
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} |
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help(); |
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int M = getOptimalDFTSize( img.rows ); |
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int N = getOptimalDFTSize( img.cols ); |
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Mat padded; |
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copyMakeBorder(img, padded, 0, M - img.rows, 0, N - img.cols, BORDER_CONSTANT, Scalar::all(0)); |
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Mat planes[] = {Mat_<float>(padded), Mat::zeros(padded.size(), CV_32F)}; |
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Mat complexImg; |
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merge(planes, 2, complexImg); |
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dft(complexImg, complexImg); |
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// compute log(1 + sqrt(Re(DFT(img))**2 + Im(DFT(img))**2)) |
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split(complexImg, planes); |
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magnitude(planes[0], planes[1], planes[0]); |
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Mat mag = planes[0]; |
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mag += Scalar::all(1); |
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log(mag, mag); |
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// crop the spectrum, if it has an odd number of rows or columns |
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mag = mag(Rect(0, 0, mag.cols & -2, mag.rows & -2)); |
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int cx = mag.cols/2; |
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int cy = mag.rows/2; |
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// rearrange the quadrants of Fourier image |
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// so that the origin is at the image center |
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Mat tmp; |
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Mat q0(mag, Rect(0, 0, cx, cy)); |
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Mat q1(mag, Rect(cx, 0, cx, cy)); |
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Mat q2(mag, Rect(0, cy, cx, cy)); |
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Mat q3(mag, Rect(cx, cy, cx, cy)); |
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q0.copyTo(tmp); |
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q3.copyTo(q0); |
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tmp.copyTo(q3); |
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q1.copyTo(tmp); |
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q2.copyTo(q1); |
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tmp.copyTo(q2); |
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normalize(mag, mag, 0, 1, CV_MINMAX); |
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imshow("spectrum magnitude", mag); |
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waitKey(); |
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return 0; |
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} |
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