#include "opencv2/core.hpp" #include "opencv2/core/utility.hpp" #include "opencv2/imgproc.hpp" #include "opencv2/imgcodecs.hpp" #include "opencv2/highgui.hpp" #include #include #include 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) { //int cols = 4; //int rows = 768; //srand(0); //Mat input(Size(cols, rows), CV_32FC2); //for (int i=0; i(j,i) = Vec2f((float) rand() / RAND_MAX, (float) rand() / RAND_MAX); //Mat dst; // //UMat gpu_input, gpu_dst; //input.copyTo(gpu_input); //auto start = std::chrono::system_clock::now(); //dft(input, dst, DFT_ROWS); //auto cpu_duration = chrono::duration_cast(chrono::system_clock::now() - start); // //start = std::chrono::system_clock::now(); //dft(gpu_input, gpu_dst, DFT_ROWS); //auto gpu_duration = chrono::duration_cast(chrono::system_clock::now() - start); //double n = norm(dst, gpu_dst); //cout << "norm = " << n << endl; //cout << "CPU time: " << cpu_duration.count() << "ms" << endl; //cout << "GPU time: " << gpu_duration.count() << "ms" << endl; help(); CommandLineParser parser(argc, argv, keys); string filename = parser.get(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; } Mat small_img = img(Rect(0,0,6,6)); int M = getOptimalDFTSize( small_img.rows ); int N = getOptimalDFTSize( small_img.cols ); Mat padded; copyMakeBorder(small_img, padded, 0, M - small_img.rows, 0, N - small_img.cols, BORDER_CONSTANT, Scalar::all(0)); Mat planes[] = {Mat_(padded), Mat::ones(padded.size(), CV_32F)}; Mat complexImg, complexImg1, complexInput; merge(planes, 2, complexImg); Mat realInput; padded.convertTo(realInput, CV_32F); complexInput = complexImg; //cout << complexImg << endl; //dft(complexImg, complexImg, DFT_REAL_OUTPUT); //cout << "Complex to Complex" << endl; //cout << complexImg << endl; cout << "Complex input" << endl << complexInput << endl; cout << "Real input" << endl << realInput << endl; dft(complexInput, complexImg1, DFT_COMPLEX_OUTPUT); cout << "Complex to Complex image: " << endl; cout << endl << complexImg1 << endl; Mat realImg1; dft(complexInput, realImg1, DFT_REAL_OUTPUT); cout << "Complex to Real image: " << endl; cout << endl << realImg1 << endl; Mat realOut; dft(complexImg1, realOut, DFT_INVERSE | DFT_COMPLEX_OUTPUT); cout << "Complex to Complex (inverse):" << endl; cout << realOut << endl; Mat complexOut; dft(realImg1, complexOut, DFT_INVERSE | DFT_REAL_OUTPUT | DFT_SCALE); cout << "Complex to Real (inverse):" << endl; cout << complexOut << endl; // 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; }