#include "iostream"
#include "math.h"
#include <opencv2/opencv.hpp>

using namespace std;
using namespace cv;


void gaussian(cv::Mat *_src, double **array, int _size);
double **getGaussianArray(int arr_size, double sigma);
void myGaussianFilter(cv::Mat *src, cv::Mat *dst, int n, double sigma);


int main(void)
{
    cv::Mat src1 = cv::imread("E:/2020/test12.jpg");
    cv::Mat src;
    cvtColor(src1, src, COLOR_BGR2GRAY);
    cv::Mat dst;
    myGaussianFilter(&src, &dst, 5, 3.5f);

    cv::imshow("src", src);
    cv::imshow("dst", dst);
    cv::waitKey(0);
    cv::destroyAllWindows();

    return 0;

}

void myGaussianFilter(cv::Mat *src, cv::Mat *dst, int n, double sigma) {
    *dst = (*src).clone();
    std::vector<cv::Mat> channels;
    cv::split(*src, channels);
    double ** array = getGaussianArray(n, sigma);
    for (int i = 0; i < 1; i++) {
        gaussian(&channels[i], array, n);
    }
    cv::merge(channels, *dst);
    return;
}


//******************高斯卷积核生成函数*************************
/* 获取高斯分布数组               (核大小， sigma值) */
double **getGaussianArray(int arr_size, double sigma)
{
    int i, j;
    // [1] 初始化权值数组
    double **array = new double*[arr_size];
    for (i = 0; i < arr_size; i++) {
        array[i] = new double[arr_size];
    }
    // [2] 高斯分布计算
    int center_i, center_j;
    center_i = center_j = arr_size ;
    double pi = 3.141592653589793238462643383279502884197;
    double sum = 0.0f;
    // [2-1] 高斯函数
    for (i = 0; i < 1; i++) {
        for (j = 0; j < arr_size; j++) {
            array[i][j] =
                //后面进行归一化，这部分可以不用
                //0.5f *pi*(sigma*sigma) * 
                exp(-(1.0f)* (((i - center_i)*(i - center_i) + (j - center_j)*(j - center_j)) /
                (2.0f*sigma*sigma)));
            sum += array[i][j];
        }
    }
    // [2-2] 归一化求权值
    for (i = 0; i < 1; i++) {
        for (j = 0; j < arr_size; j++) {
            array[i][j] /= sum;
            printf(" [%.15f] ", array[i][j]);
        }
        printf("\n");
    }
    return array;
}

//高斯滤波
/* 高斯滤波 (待处理单通道图片, 高斯分布数组， 高斯数组大小(核大小) ) */
void gaussian(cv::Mat *_src, double **_array, int _size)
{
    cv::Mat temp = (*_src).clone();
    for (int i = 0; i < (*_src).rows; i++) {
        for (int j = _size - 1; j < (*_src).cols; j++) {
            double sum = 0.0;
            for (int k = 0; k < _size; k++) {
                sum += (*_src).ptr<uchar>(i)[j - (_size) + 1 + k] * _array[0][k];
            }
            //cout << "sum= " << sum << endl;
            temp.ptr<uchar>(i)[j] = sum;
        }
    }
    (*_src) = temp.clone();
}

参考链接