OpenCV 图像线性滤波综合示例程序(用到了Trackbar轨迹条)

http://blog.csdn.net/poem_qianmo/article/details/22745559

//-----------------------------------【程序说明】----------------------------------------------//            程序名称:：【OpenCV入门教程之八】线性滤波专场：方框滤波、均值滤波与高斯滤波 //------------------------------------------------------------------------------------------------//-----------------------------------【头文件包含部分】---------------------------------------//     描述：包含程序所依赖的头文件//----------------------------------------------------------------------------------------------#include <opencv2/core/core.hpp>#include<opencv2/highgui/highgui.hpp>#include <opencv2/imgproc/imgproc.hpp>#include <iostream>//-----------------------------------【命名空间声明部分】---------------------------------------//     描述：包含程序所使用的命名空间//----------------------------------------------------------------------------------------------- using namespace std;using namespace cv;//-----------------------------------【全局变量声明部分】--------------------------------------//     描述：全局变量声明//-----------------------------------------------------------------------------------------------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】--------------------------------------//     描述：全局函数声明//-----------------------------------------------------------------------------------------------//轨迹条的回调函数static void on_BoxFilter(int, void *);          //方框滤波static void on_MeanBlur(int, void *);           //均值滤波static void on_GaussianBlur(int, void *);       //高斯滤波//-----------------------------------【main( )函数】--------------------------------------------//     描述：控制台应用程序的入口函数，我们的程序从这里开始//-----------------------------------------------------------------------------------------------int main(){//改变console字体颜色system("color5E");//载入原图g_srcImage = imread("yun.jpg");if (!g_srcImage.data) { printf("Oh，no，读取srcImage错误~！\n"); return false; }//克隆原图到三个Mat类型中 深拷贝g_dstImage1 = g_srcImage.clone();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_MeanBlur(g_nBoxFilterValue, 0);imshow("【<1>方框滤波】", g_dstImage1);//================================================//=================【<2>均值滤波】==================//创建窗口namedWindow("【<2>均值滤波】", 1);//创建轨迹条createTrackbar("内核值：", "【<2>均值滤波】", &g_nMeanBlurValue, 40, on_MeanBlur);on_MeanBlur(g_nMeanBlurValue, 0);//================================================//=================【<3>高斯滤波】=====================//创建窗口namedWindow("【<3>高斯滤波】", 1);//创建轨迹条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嗯。好了，请调整滚动条观察图像效果~\n\n";waitKey();return 0;}//-----------------------------【on_BoxFilter( )函数】------------------------------------//     描述：方框滤波操作的回调函数//-----------------------------------------------------------------------------------------------static void on_BoxFilter(int, void *){//方框滤波操作boxFilter(g_srcImage, g_dstImage1, -1, Size(g_nBoxFilterValue + 1, g_nBoxFilterValue + 1));//显示窗口imshow("【<1>方框滤波】", g_dstImage1);}//-----------------------------【on_MeanBlur( )函数】------------------------------------//     描述：均值滤波操作的回调函数//-----------------------------------------------------------------------------------------------static void on_MeanBlur(int, void *){//均值滤波操作blur(g_srcImage, g_dstImage2, Size(g_nMeanBlurValue + 1, g_nMeanBlurValue + 1), Point(-1, -1));//显示窗口imshow("【<2>均值滤波】", g_dstImage2);}//-----------------------------【on_GaussianBlur( )函数】------------------------------------//     描述：高斯滤波操作的回调函数//-----------------------------------------------------------------------------------------------static void on_GaussianBlur(int, void *){//高斯滤波操作GaussianBlur(g_srcImage, g_dstImage3, Size(g_nGaussianBlurValue * 2 + 1, g_nGaussianBlurValue * 2 + 1), 0, 0);//显示窗口imshow("【<3>高斯滤波】", g_dstImage3);}