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