#include <iostream> #include <opencv2corecore.hpp> #include <opencv2highguihighgui.hpp> #include <opencv2imgprocimgproc.hpp> using namespace std; using namespace cv; Mat g_srcImage; // 全局的源图像 // 分别对应全局的方框滤波、均值滤波、高斯滤波、中值滤波、双边滤波的输出图像以及内核值/参数值 Mat g_dstImgBox, g_dstImgBlur, g_dstImgGaussian, g_dstImgMedian, g_dstImgBilateral; int g_BoxFilterVal = 5; int g_BlurVal = 12; int g_GaussianBlurVal = 5; int g_MedianBlurVal = 12; int g_BilateralFilterVal = 12; static void on_BoxFilter(int, void *); static void on_Blur(int, void *); static void on_GaussianBlur(int, void *); static void on_MedianBlur(int, void *); static void on_BilateralFilter(int, void*); int main() { // 读取图像到g_srcImage g_srcImage = imread("6013202130.jpg"); if (!g_srcImage.data) { printf("读取的图片不存在…… "); return false; } // 分别克隆原图到5中滤波所需的图像中,均为Mat类型 g_dstImgBox = g_srcImage.clone(); g_dstImgBlur = g_srcImage.clone(); g_dstImgGaussian = g_srcImage.clone(); g_dstImgMedian = g_srcImage.clone(); g_dstImgBilateral = g_srcImage.clone(); // 显示原图 namedWindow("【原图】", 1); imshow("【原图】", g_srcImage); namedWindow("【均值滤波】", 1); createTrackbar("内核值", "【均值滤波】", &g_BlurVal, 30, on_Blur); on_Blur(g_BlurVal, 0); namedWindow("【高斯滤波】", 1); createTrackbar("内核值", "【高斯滤波】", &g_GaussianBlurVal, 30, on_GaussianBlur); on_GaussianBlur(g_GaussianBlurVal, 0); namedWindow("【中值滤波】", 1); createTrackbar("内核值", "【中值滤波】", &g_MedianBlurVal, 30, on_MedianBlur); on_MedianBlur(g_MedianBlurVal, 0); cout << "按下“q”键时,程序退出…… "; while (char(waitKey(1)) != 'q') {} return 0; } static void on_Blur(int, void *) { blur(g_srcImage, g_dstImgBlur, Size(g_BlurVal + 1, g_BlurVal + 1), Point(-1, -1)); imshow("【均值滤波】", g_dstImgBlur); } static void on_GaussianBlur(int, void *) { GaussianBlur(g_srcImage, g_dstImgGaussian, Size(g_GaussianBlurVal * 2 + 1, g_GaussianBlurVal * 2 + 1), 0, 0); imshow("【高斯滤波】", g_dstImgGaussian); } static void on_MedianBlur(int, void *) { medianBlur(g_srcImage, g_dstImgMedian, g_MedianBlurVal * 2 + 1); imshow("【中值滤波】", g_dstImgMedian); }