【c++|opencv】二、灰度变换和空间滤波---4.高斯滤波

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https://blog.csdn.net/weixin_39190382?type=blog

0. 前言

1. 高斯滤波

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

using namespace std;
using namespace cv;

// 定义高斯滤波函数
void myfilter(int filter_size,Mat& img_input,Mat& img_output);


int main(){
    
    
    Mat img,img_gray,img_out,img_out2;
    img = imread("/home/v/home.png");
    if (img.empty()){
    
    
        cout<<"can't open the image"<<endl;
        return -1;
    }
    imshow("img",img);
    cvtColor(img,img_gray,COLOR_BGR2GRAY);
    Salt(img_gray,1000);
    imshow("img_gray",img_gray);

    // Opencv 自带的滤波
    int a= 7;
    GaussianBlur(img_gray,img_out,Size(a,a),2,2);
    imshow("GaussianBlur",img_out);

    // 自定义高斯滤波
    myfilter(a,img_gray,img_out2);
    imshow("myfilter",img_out2);
    waitKey(0);
    return 0;
}

void myfilter(int filter_size,Mat& img_input,Mat& img_output){
    
    

    img_output = img_input.clone();
    int k = (filter_size-1)/2;

    for (int i = k; i < img_input.rows-k; i++){
    
    
        for (int j = k; j < img_input.cols-k; j++){
    
    
            double sum = 0.0;
            double sum1 = 0.0;
            double sigma = 7;
            double g;

            for (int m = -k; m <= k; m++){
    
    
                for (int n = -k; n <= k; n++){
    
    
                    g = exp(-(m*m+n*n)/(2*sigma*sigma));
                    sum += g*img_input.at<uchar>(i+m,j+n);
                    sum1 += g;
                }
            }
            img_output.at<uchar>(i,j) = (int)(sum/sum1);
        }
   }


}