Gaussian-Filter/convolution.cpp at master · amh28/Gaussian-Filter · GitHub

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#include <stdio.h>
#include <iostream>
#include "CImg.h"
#include <math.h>
#include <chrono>

using namespace std;
using namespace cimg_library;


typedef CImg<unsigned char> IC;
typedef CImg<float> IF;
typedef float F;
typedef int I;


template <size_t s>
IF convolution(IC img, int mask[s][s], int size)
{
	IF imgt(img.width(), img.height(),1,3,0);
	float dim = size*1.0;
	size/=2;
	cout<<"size: "<<size<<endl;
	for (int i = size; i<img.width() - size; i++)
		for (int j = size; j<img.height() - size; j++)
		{
			float cont1 = 0.0, cont2 = 0.0, cont3 = 0.0;
			for (int k = -size; k <= size; k++)
			{
				for (int k1 = -size; k1 <= size; k1++)
				{
					cont1 += (img(i + k1, j + k, 0)*mask[k1 + size][k + size]);
					cont2 += (img(i + k1, j + k, 1)*mask[k1 + size][k + size]);
					cont3 += (img(i + k1, j + k, 2)*mask[k1 + size][k + size]);
				}

			}

			//cout<<cont1<<" "<<cont2<<" "<<cont3<<endl;
			cont1 *= 1.0;
			cont2 *= 1.0;
			cont3 *= 1.0;

			cont1 /= dim;
			cont2 /= dim;
			cont3 /= dim;

			imgt(i, j,0) = cont1;
			imgt(i, j,1) = cont2;
			imgt(i, j,2) = cont3;

			//if(j==size) break;
		}
	img.get_normalize(0,255);
	return imgt;
}


int main()
{
	IC img("ironman.bmp");

	int gx[3][3] = { { -1, -2, -1 }, { 0, 0, 0 }, { 1, 2, 1 } };
	int gy[3][3] = { { 1, 0, -1 }, { 2, 0, -2 }, { 1, 0, -1 } };
	int s3[3][3] = { { 1, 1, 1 }, { 1, 1, 1}, { 1, 1, 1 } };
	int s5[5][5] = { {1, 1, 1, 1,1 }, { 1,1, 1, 1,1}, { 1,1, 1, 1,1 }, { 1,1, 1, 1,1 }, { 1,1, 1, 1,1 }};
	int s7[7][7] = { {1, 1, 1, 1,1,1,1 }, {1,1, 1, 1,1,1,1}, { 1,1, 1, 1,1,1,1 }, { 1,1, 1, 1,1,1,1 }, { 1,1, 1, 1,1,1,1 }, { 1,1, 1, 1,1,1,1 }, { 1,1, 1, 1,1,1,1 }};
	int s11[11][11] = { {1, 1, 1, 1,1,1,1,1,1,1,1 }, {1,1, 1, 1,1,1,1,1,1,1,1}, {1,1, 1, 1,1,1,1,1,1,1,1}, {1,1, 1, 1,1,1,1,1,1,1,1}, {1,1,1,1,1,1,1,1,1,1,1 },
					 { 1,1, 1, 1,1,1,1,1,1,1,1 }, {1,1, 1, 1,1,1,1,1,1,1,1}, {1,1, 1, 1,1,1,1,1,1,1,1}, {1,1, 1, 1,1,1,1,1,1,1,1}, {1,1,1,1,1,1,1,1,1,1,1}, {1,1,1,1,1,1,1,1,1,1,1} };


	auto start_time = std::chrono::high_resolution_clock::now();
	//IF smooth = convolution<3>(img,s3,3);
	IF smooth = convolution<5>(img,s5,5);
	//IF smooth = convolution<7>(img,s7,7);
	//IF smooth = convolution<11>(img,s11,11);

	auto end_time = std::chrono::high_resolution_clock::now();
	auto time = end_time - start_time;
	std::cout << "Secuential took " << std::chrono::duration_cast<std::chrono::milliseconds>(time).count() << " to run.\n";


	smooth.display();
	img.display();


	return 0;

}