//////////////////////////////////////////////////////////////////////////////// // Empirical Mode Decomposition // // BERNARD Guillaume // // DURAND William // // ZZ3F2 ISIMA // //////////////////////////////////////////////////////////////////////////////// #include "CImg.h" #include #include #include #include "Euclidean.hpp" #define MAX_ITERATIONS 3 // Variance delta #define DELTA 50 #define MIN(x,y) ((x)<(y)?(x):(y)) #define MAX(x,y) ((x)>(y)?(x):(y)) using namespace cimg_library; int SIZE = 3; double sum(CImg img, int startedX, int startedY, int w) { double res = 0; for (int i = startedX - ((w - 1) / 2); i < startedX + ((w + 1) / 2); i++) { for (int j = startedY - ((w - 1) / 2) ; j < startedY + ((w + 1) / 2); j++) { if ((i >= 0 && i < img.width()) && (j >= 0 && j < img.height())) { res += img(i,j); } } } return res; } CImg decompose(const CImg input) { /////////////////////////////////////////////////////////////////////////////// // Part 1: Finding minimas and maximas // /////////////////////////////////////////////////////////////////////////////// std::vector vectEMax, vectEMin; CImg imgMax(input.width(), input.height()); CImg imgMin(input.width(), input.height()); for (int i = 0; i < input.width(); i += SIZE) for (int j = 0; j < input.height(); j += SIZE) { // Save max and min locations int xmin=i, xmax=i, ymin=j, ymax=j; float min = input(i,j), max = input(i,j); imgMax(i,j) = input(i,j); imgMin(i,j) = input(i,j); // SIZExSIZE for (int k = i; k < i + SIZE; k++) for (int l = j; l < j + SIZE; l++) { // Max if ((input(k, l) > max) && (l != ymax || k != xmax)) { imgMax(xmax, ymax) = 0; max = input(k, l); imgMax(k,l) = max; xmax = k; ymax = l; } // Min if ((imgMin(k, l) < min) && (l != ymin || k != xmin)) { imgMax(xmax, ymax) = 0; min = imgMin(k, l); imgMax(k,l) = max; xmin = k; ymin = l; } } vectEMax.push_back(Euclidean(xmax,ymax)); vectEMin.push_back(Euclidean(xmin,ymin)); } // Array of Euclidean distance to the nearest non zero element std::vector::iterator it1, it2; for (it1 = vectEMax.begin(); it1 != vectEMax.end(); it1++) for (it2 = it1 + 1; it2 != vectEMax.end(); it2++) { double dist = (*it1).computeDistanceFrom(*it2); if ((*it1).getDistance() == 0 || dist < (*it1).getDistance()) { (*it1).setDistance(dist); (*it1).setNearest(*it2); } if ((*it2).getDistance() == 0 || dist < (*it2).getDistance()) { (*it2).setDistance(dist); (*it2).setNearest(*it1); } } for (it1 = vectEMin.begin(); it1 != vectEMin.end(); it1++) for (it2 = it1 + 1; it2 != vectEMin.end(); it2++) { double dist = (*it1).computeDistanceFrom(*it2); if ((*it1).getDistance() == 0 || dist < (*it1).getDistance()) { (*it1).setDistance(dist); (*it1).setNearest(*it2); } if ((*it2).getDistance() == 0 || dist < (*it2).getDistance()) { (*it2).setDistance(dist); (*it2).setNearest(*it1); } } // Calculate the window size double d = MAX(Euclidean::max(vectEMax), Euclidean::max(vectEMin)); int wmax = 2*((int)d/2)+1; // Order filters with source image std::vector vectFilterMax, vectFilterMin; for(int unsigned i = 0; i < vectEMax.size(); i++) { float max = 0; for (int k = vectEMax[i].getX() - ((wmax - 1) / 2); k < vectEMax[i].getX() + ((wmax + 1) / 2); k++) { for (int l = vectEMax[i].getY() - ((wmax - 1) / 2); l < vectEMax[i].getY() + ((wmax + 1) / 2); l++) { if( (k >= 0 && k < input.width()) && (l >= 0 && l < input.height()) ) { if (input(k, l) > max) { max = input(k, l); } } } } vectFilterMax.push_back(max); } for(int unsigned i = 0; i < vectEMin.size(); i++) { float min = 255; for (int k = vectEMin[i].getX() - ((wmax - 1) / 2); k <= vectEMin[i].getX() + ((wmax + 1) / 2); k++) { for (int l = vectEMin[i].getY() - ((wmax - 1) / 2); l < vectEMin[i].getY() + ((wmax + 1) / 2); l++) { if( (k >= 0 && k < input.width()) && (l >= 0 && l < input.height()) ) { if (input(k, l) < min) { min = input(k, l); } } } } vectFilterMin.push_back(min); } // Calculate the upper envelope CImg newImgMax(imgMax.width(), imgMax.height()); for(int unsigned i = 0; i < vectEMax.size(); i++) { for (int k = vectEMax[i].getX() - ((wmax - 1) / 2); k < vectEMax[i].getX() + ((wmax + 1) / 2); k++) { for (int l = vectEMax[i].getY() - ((wmax - 1) / 2); l < vectEMax[i].getY() + ((wmax + 1) / 2); l++) { if ((k >= 0 && k < input.width()) && (l >= 0 && l < input.height())) { if (imgMax(k, l) == 0) imgMax(k, l) = vectFilterMax[i]; else imgMax(k, l) = (int)((imgMax(k, l) + vectFilterMax[i]) / 2); } } } } // Smooth of the upper envelope for (int k = 0; k < input.width(); k++) { for (int l = 0; l < input.height(); l++) { if( (k >= 0 && k < input.width()) && (l >= 0 && l < input.height()) ) { newImgMax(k, l) = (int)sum(imgMax, k, l, wmax) / (wmax * wmax); } } } // Calculate the lower envelope CImg newImgMin(imgMin.width(), imgMin.height()); for(int unsigned i = 0; i < vectEMin.size(); i++) { for (int k = vectEMin[i].getX() - ((wmax - 1) / 2); k < vectEMin[i].getX() + ((wmax + 1) / 2); k++) { for (int l = vectEMin[i].getY() - ((wmax - 1) / 2); l < vectEMin[i].getY() + ((wmax + 1) / 2); l++) { if( (k >= 0 && k < input.width()) && (l >= 0 && l < input.height()) ) { if( imgMin(k, l) == 0 ) imgMin(k, l) = vectFilterMin[i]; else imgMin(k, l) = (int)((imgMin(k, l) + vectFilterMin[i]) / 2); } } } } // Smooth of the lower envelope for (int k = 0; k < input.width(); k++) { for (int l = 0; l < input.height(); l++) { if( (k >= 0 && k < input.width()) && (l >= 0 && l < input.height()) ) { newImgMin(k, l) = (int)sum(imgMin, k, l, wmax) / (wmax * wmax); } } } /////////////////////////////////////////////////////////////////////////////// // Part 2: Average // /////////////////////////////////////////////////////////////////////////////// // Calculate the Average CImg imgMoyenne(input.width(), input.height()); for (int i = 0; i < input.width(); i++) for (int j = 0; j < input.height(); j++) imgMoyenne(i, j) = (newImgMin(i, j) + newImgMax(i, j)) /2; /////////////////////////////////////////////////////////////////////////////// // Partie 3: Deletion // /////////////////////////////////////////////////////////////////////////////// return input - imgMoyenne; } /******************************************************************************* Main *******************************************************************************/ int main(int argc, char **argv) { char modeTitle[30], residueTitle[50]; double variance = 1000000; if (argc != 2) { std::cout << "Usage: ./emd " << std::endl; return 1; } CImgDisplay disp[MAX_ITERATIONS * 2 + 1]; CImg inputImg(argv[1]), imgMode; disp[0].assign(inputImg, "Source Image"); for (int i = 1; i < MAX_ITERATIONS + 1; i++) { sprintf(modeTitle, "BEMC-%d", i); std::cout << "Decomposing " << modeTitle << std::endl; // Process imgMode = decompose(inputImg); inputImg = inputImg - imgMode; // Display BEMC i disp[i].assign(imgMode, modeTitle); // Display residue sprintf(residueTitle, "Residue %s", modeTitle); disp[MAX_ITERATIONS + i].assign(inputImg, residueTitle); // Get variance std::cout << "Variance: " << inputImg.variance() << std::endl; if (fabs(variance - inputImg.variance()) < DELTA) { std::cout << "Ended at iteration " << i << std::endl; break; } else { variance = inputImg.variance(); } } while (!disp[0].is_closed()) { disp[0].wait(); } return 0; }