OpenCV实现图象翻转、滤波、锐化

OpenCV实现图象翻转、滤波、锐化

注：以下代码，使用opencv库函数实现了对图片的翻转、灰度图转换、各种滤波、各种锐化。

库函数相关参数及说明参阅：OpenCV中文站=》opencv教程（cn）

 #include <iostream>
 #include <stdio.h>
 #include <Windows.h>
 #include <opencv2/highgui/highgui.hpp>
 #include <opencv2/imgproc/imgproc.hpp>
 #include <opencv2/imgproc/types_c.h>
 #include <opencv2/core/core.hpp>
 #include <opencv2/opencv.hpp>

 using namespace std;
 using namespace cv;

 //全局变量
 const int slider_max = ;
 int slider;
 Mat img;
 Mat resImg;

 Mat src, res[];

 //翻转图片
 void turn(string src)
 {
     Mat srcMat = imread(src);
     if (!srcMat.data)
     {
         cout << "源图象获取失败!" << endl;
         return;
     }
     //原始图像
     imshow("原图片", srcMat);
     //水平翻转
     flip(srcMat, res[], );
     imshow("水平翻转", res[]);
     imwrite("D:\\trashBox\\testIMG\\flip1.jpg", res[]);
     //垂直翻转
     flip(srcMat, res[], );
     imshow("垂直翻转", res[]);
     imwrite("D:\\trashBox\\testIMG\\flip0.jpg", res[]);
 }

 //图像平滑处理（滤波）
 void blur(string src)
 {
     Mat srcMat = imread(src);
     if (!srcMat.data)
     {
         cout << "源图象获取失败!" << endl;
         return;
     }
     //源图片
     imshow("源图片", srcMat);
     //中值滤波
     medianBlur(srcMat, res[], );
     imshow("中值滤波", res[]);
     imwrite("D:\\trashBox\\testIMG\\medianBlur.jpg", res[]);
     //均值滤波
     blur(srcMat, res[], Size(, ), Point(-, -));
     imshow("均值滤波", res[]);
     imwrite("D:\\trashBox\\testIMG\\averBlur.jpg", res[]);
     //高斯滤波
     GaussianBlur(srcMat, res[], Size(, ), , );
     imshow("高斯滤波", res[]);
     imwrite("D:\\trashBox\\testIMG\\gsBlur.jpeg", res[]);
 }

 //图象锐化:高通滤波
 void sharpen(string src)
 {
     Mat srcMat = imread(src);
     if (!srcMat.data)
     {
         cout << "源图象获取失败!" << endl;
         return;
     }
     //原图
     imshow("源图片", srcMat);
     //灰度图
     cvtColor(srcMat, res[], CV_BGR2GRAY);
     imshow("灰度图象", res[]);
     imwrite("D:\\trashBox\\testIMG\\grey.jpg", res[]);
     //sobel算子,基于梯度
     Sobel(res[], res[], res[].depth(), , , , , , BORDER_DEFAULT);
     imshow("X水平Sobel", res[]);
     imwrite("D:\\trashBox\\testIMG\\sobelX.jpg", res[]);
     Sobel(res[], res[], res[].depth(), , , , , , BORDER_DEFAULT);
     imshow("Y方向Sobel", res[]);
     imwrite("D:\\trashBox\\testIMG\\sobelY.jpg", res[]);
     //sobel叠加
     convertScaleAbs(res[], res[]);
     convertScaleAbs(res[], res[]);
     addWeighted(res[], 0.5, res[], 0.5, , res[]);
     imshow("叠加Sobel", res[]);
     imwrite("D:\\trashBox\\testIMG\\sobelXY.jpg", res[]);

     //laplace算子， 基于二阶微分
     Laplacian(res[], res[], res[].depth(), , , , BORDER_DEFAULT);
     convertScaleAbs(res[], res[]);
     imshow("Laplace算子边缘检测", res[]);
     imwrite("D:\\trashBox\\testIMG\\laplace.jpg", res[]);
 }

 //直方图
 void hist(string src)
 {
     Mat srcMat = imread(src);
     if (!srcMat.data)
     {
         cout << "源图象获取失败!" << endl;
         return;
     }
     //直方图均衡化
     cvtColor(srcMat, res[], CV_BGR2GRAY);//转灰度图像
     imshow("灰度图", res[]);
     equalizeHist(res[], res[]);
     imshow("直方图均衡化", res[]);
     imwrite("D:\\trashBox\\equalHist.jpg", res[]);
 }

 //颜色减半
 void colorReduce(Mat& input, Mat& output, int div);
 void on_trackbar(int pos, void *);

 //迭代器实现颜色减半
 void colorReduce(Mat& input, Mat& output, int div)
 {
     output = input.clone();

     Mat_<Vec3b>::iterator it = input.begin<Vec3b>();
     Mat_<Vec3b>::iterator itend = input.end<Vec3b>();

     Mat_<Vec3b> cimage = output;
     Mat_<Vec3b>::iterator itout = cimage.begin();
     Mat_<Vec3b>::iterator itoutend = cimage.end();

     for (; it != itend; it++, itout++)
     {
         for(int i=; i<; i++)
             (*itout)[i] = (*it)[i] / div * div + div / ;//200-249->0-29压缩灰度级，用中间值代替
     }
     //output = cimage;
     //imshow("源图片", input);
     //imshow("颜色减半图片", output);
 }

 //trackBar 回调函数
 void on_trackbar(int pos, void *)
 {
     if (pos <= )
     {
         resImg = img;
     }
     else
     {
         colorReduce(img, resImg, pos);
     }
     imshow("显示结果", resImg);
 }

 int main()
 {
　　　　 //**************此部分代码调用翻转、滤波、锐化函数*******************//
     //string lena = "D:\\trashBox\\testIMG\\lena.bmp";
     //string tiger = "D:\\trashBox\\testIMG\\tiger.jpg";
     //string xian = "D:\\trashBox\\testIMG\\xian.jpg";
     //turn(lena);
     //blur(tiger);
     //blur(lena);
     //sharpen(xian);
     //sharpen(xian);
     //hist(lena);
　　　　 //**************************************************************//

        //********************此部分代码实现图象的颜色减半******************//
     Mat src, res;
     img = imread("D:\\trashBox\\photo.jpg");
     if (!img.data)
     {
         cout << "源图象获取失败!" << endl;
         return ;
     }
     namedWindow("原图像");
     namedWindow("显示结果");

     slider = ;
     createTrackbar("ColorReduce", "显示结果", &slider, slider_max, on_trackbar);

     imshow("原图像", img);
     imshow("显示结果", img);

     waitKey();
 }