图像线性滤波的综合 滑动条控制三种线性滤波的核参数值

#include<opencv2/opencv.hpp>
#include<iostream>

using namespace cv;
using namespace std;

Mat src;  // 原图像声明
Mat dst1_image, dst2_image, dst3_image;  //三种滤波函数的目标图像声明

int BoxFilterValue = 3;// 方框滤波参数值
int MeanFilterValue = 3; //均值滤波参数值
int GaussianFilterValue = 3;//高斯滤波参数值

//轨迹条的回调函数
static void BoxFilter(int, void *);
static void MeanFilter(int, void *);
static void GaussianFilter(int, void *);

int main()
{   
    system("color5E");
     src = imread("D:/meinv.jpg");
    cvNamedWindow("原图像", CV_WINDOW_AUTOSIZE);
    
    imshow("原图像", src);

    //复制原图到三个目标图像中
    dst1_image = src.clone();    
    dst2_image = src.clone();
    dst3_image = src.clone();
     
    //方框滤波
    namedWindow("方框滤波", 1);
    //创建轨迹条
    createTrackbar("内核值：", "方框滤波",&BoxFilterValue,40, BoxFilter);
    BoxFilter(BoxFilterValue, 0);

    //均值滤波
    namedWindow("均值滤波", 1);
    createTrackbar("内核值：", "均值滤波", &MeanFilterValue, 40, MeanFilter);
    MeanFilter(MeanFilterValue, 0);

    //高斯滤波
    namedWindow("高斯滤波", 1);
    createTrackbar("内核值：", "高斯滤波", &GaussianFilterValue, 40, GaussianFilter);
    GaussianFilter(GaussianFilterValue, 0);
    
    waitKey(0);
    return 0;
}

static void BoxFilter(int, void *)
{
    
    boxFilter(src, dst1_image, -1, Size(BoxFilterValue + 1, BoxFilterValue + 1));
    imshow("方框滤波", dst1_image);
}

static void MeanFilter(int, void *)
{
    blur(src, dst2_image,Size(MeanFilterValue + 1, MeanFilterValue + 1),Point(-1,-1));
    imshow("均值滤波", dst2_image);
}

static void GaussianFilter(int, void *)
{
    GaussianBlur(src, dst3_image, Size(GaussianFilterValue*2 + 1, GaussianFilterValue*2 + 1), 0,0);
    imshow("高斯滤波", dst3_image);
    imwrite("D:/learn-opencv/gaussian.jpg", dst3_image);
}