#include <opencv2/opencv.hpp>
using namespace std;
using namespace cv;
//全局变量声明部分
Mat g_srcImage, g_dstImage1, g_dstImage2, g_dstImage3;//存储图片的Mat类型
int g_nBoxFilterValue = 3;//方框滤波参数值
int g_nMeanBlurValue = 3;//均值滤波参数值
int g_nGaussianBlurValue = 3;//高斯滤波参数值
//全局函数声明部分
static void on_BoxFilter(int, void *);
static void on_MeanBlur(int, void *);
static void on_GaussianBlur(int, void *);
//main()函数
int main() {
//改变console字体颜色
system("color5E");
//载入原图
g_srcImage = imread("1.jpg", 1);//载入三通道彩色图像
if (!g_srcImage.data) {
printf("读取srcImage错误!\n");
return false;
}
//复制原图到三个Mat类型中
g_dstImage1 = g_srcImage.clone();//初始化目标图像大小,类型
g_dstImage2 = g_srcImage.clone();
g_dstImage3 = g_srcImage.clone();
//显示原图
namedWindow("<0>原图窗口",1);
imshow("<0>原图窗口", g_srcImage);
//====================【<1>方框滤波】=====================
//创建窗口
namedWindow("<1>方框滤波", 1);
//创建轨迹条
createTrackbar("内核值:", "<1>方框滤波", &g_nBoxFilterValue, 40, on_BoxFilter);
on_BoxFilter(g_nBoxFilterValue, 0);//回调函数参数初始化
//=========================================================
//=====================【<2>均值滤波】=====================
namedWindow("<2>均值滤波", 1);
createTrackbar("内核值:", "<2>均值滤波", &g_nMeanBlurValue, 40, on_MeanBlur);
on_MeanBlur(g_nMeanBlurValue, 0);
//=========================================================
//=====================【<3>高斯滤波】=====================
namedWindow("<3>高斯滤波", 1);
createTrackbar("内核值:", "<3>高斯滤波", &g_nGaussianBlurValue, 40, on_GaussianBlur);
on_GaussianBlur(g_nGaussianBlurValue, 0);
//=========================================================
//输出一些帮助信息
cout << endl << "\t,请调整轨迹条观察图像效果!\n\n" << "\t按下‘Q’键,程序退出!\n";
//按下Q键程序退出
while(char(waitKey(1))!='q'){
}
return 0;
}
//=======================【on_BoxFilter()函数】==============================
static void on_BoxFilter(int, void *) {
//回调函数参数格式
//方框滤波操作
boxFilter(g_srcImage, g_dstImage1, -1, Size(g_nBoxFilterValue + 1, g_nBoxFilterValue + 1));//ddepth=1,dst为原图深
//显示窗口
imshow("<1>方框滤波", g_dstImage1);
}
//=======================【on_MeanBlur()函数】===============================
static void on_MeanBlur(int, void *) {
blur(g_srcImage, g_dstImage2, Size(g_nMeanBlurValue + 1, g_nMeanBlurValue + 1), Point(-1, -1));
imshow("<2>均值滤波", g_dstImage2);
}
//=======================【on_GaussianBlur()函数】===========================
static void on_GaussianBlur(int, void *) {
GaussianBlur(g_srcImage, g_dstImage3, Size(g_nGaussianBlurValue*2 + 1, g_nGaussianBlurValue*2 + 1), 0, 0);
imshow("<3>高斯滤波", g_dstImage3);
}
opencv图像线性滤波综合示例(方框,均值,高斯)
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转载自blog.csdn.net/qq_43570528/article/details/100636348
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