vs2015+opencv3.3.1 实现 c++ 彩色高斯滤波器（Gaussian Smoothing, Gaussian Blur, Gaussian Filter）

//高斯滤波器 https://github.com/scutlzk
#include <opencv2\highgui\highgui.hpp>

#include <iostream>

#include <vector>

using namespace  cv;

using namespace  std;

void Get_Gaussian_Kernel(double*& gaus_1, const int size, const double sigma_s)

{

	gaus_1 = new double[size*size];

	double **gaus = new double*[size];

	for (int i = 0; i<size; i++)gaus[i] = new double[size];

	double sum = 0;

	for (int i = -size / 2; i<size / 2 + 1; i++) {

		for (int j = -size / 2; j<size / 2 + 1; j++) {

			gaus[i + size / 2][j + size / 2] = exp(-((i*i) + (j*j)) / (2 * sigma_s*sigma_s));

			sum += gaus[i + size / 2][j + size / 2];

		}

	}

	for (int i = 0; i<size; i++) {

		for (int j = 0; j<size; j++) {

			gaus[i][j] /= sum;

			gaus_1[i*size + j] = gaus[i][j];	//使用一维更简单

		}

	}

	return;

}

void Gaussian_Filter(const char *filename, Mat *&dst,const int size,const double sigma_s)

{

	double* templates;

	Get_Gaussian_Kernel(templates, size, sigma_s);

	Mat src = imread(filename, 3);

	dst = new Mat(src.rows, src.cols, CV_8UC3);

	namedWindow("src");

	imshow("src", src);

	for (int j = 0; j<src.rows; j++)

	{

		for (int i = 0; i<src.cols; i++)

		{

			double sum0 = 0;

			double sum1 = 0;

			double sum2 = 0;

			int index = 0;

			for (int m = j - size/2; m<j + size/2+1; m++)

			{

				for (int n = i - size / 2; n<i + size / 2 + 1; n++)

				{

					if (m<0 || n<0 || m>src.rows - 1 || n>src.cols - 1) { index++; continue; }//边缘不处理

					sum0 += src.at<Vec3b>(m, n)[0] * templates[index++];

					sum1 += src.at<Vec3b>(m, n)[1] * templates[index-1];

					sum2 += src.at<Vec3b>(m, n)[2] * templates[index-1];

				}

			}

			sum0 > 255 ? 255 : sum0;

			sum1 > 255 ? 255 : sum1;

			sum2 > 255 ? 255 : sum2;

			(*dst).at<Vec3b>(j, i)[0] = sum0;

			(*dst).at<Vec3b>(j, i)[1] = sum1;

			(*dst).at<Vec3b>(j, i)[2] = sum2;

		}

	}

	namedWindow("dst");

	imshow("dst", *dst);

	waitKey(0);

	return;

 }

int main() {

	const char *filename = "123.jpg";

	const int Gaussian_Kernel_Size = 9;

	const double sigma_s = 3;

	Mat *dst;

	Gaussian_Filter(filename, dst, Gaussian_Kernel_Size, sigma_s);

	imwrite("1234.jpg", *dst);

	return 0;

}