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 = 64;
int slider;
Mat img;
Mat resImg;

Mat src, res[20];

//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[0], 1);
    imshow("水平翻转", res[0]);
    imwrite("D:\trashBox\testIMG\flip1.jpg", res[0]);
    //垂直翻转
    flip(srcMat, res[1], 0);
    imshow("垂直翻转", res[1]);
    imwrite("D:\trashBox\testIMG\flip0.jpg", res[1]);
}

//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[4], 5);
    imshow("中值滤波", res[4]);
    imwrite("D:\trashBox\testIMG\medianBlur.jpg", res[4]);
    //均值滤波
    blur(srcMat, res[5], Size(2, 3), Point(-1, -1));
    imshow("均值滤波", res[5]);
    imwrite("D:\trashBox\testIMG\averBlur.jpg", res[5]);
    //高斯滤波
    GaussianBlur(srcMat, res[6], Size(3, 3), 0, 0);
    imshow("高斯滤波", res[6]);
    imwrite("D:\trashBox\testIMG\gsBlur.jpeg", res[6]);
}

//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[3], CV_BGR2GRAY);
    imshow("灰度图象", res[3]);
    imwrite("D:\trashBox\testIMG\grey.jpg", res[3]);
    //sobel算子,基于梯度
    Sobel(res[3], res[7], res[3].depth(), 1, 0, 3, 1, 0, BORDER_DEFAULT);
    imshow("X水平Sobel", res[7]);
    imwrite("D:\trashBox\testIMG\sobelX.jpg", res[7]);
    Sobel(res[3], res[8], res[3].depth(), 0, 1, 3, 1, 0, BORDER_DEFAULT);
    imshow("Y方向Sobel", res[8]);
    imwrite("D:\trashBox\testIMG\sobelY.jpg", res[8]);
    //sobel叠加
    convertScaleAbs(res[7], res[7]);
    convertScaleAbs(res[8], res[8]);
    addWeighted(res[7], 0.5, res[8], 0.5, 0, res[9]);
    imshow("叠加Sobel", res[9]);
    imwrite("D:\trashBox\testIMG\sobelXY.jpg", res[9]);

    //laplace算子， 基于二阶微分
    Laplacian(res[3], res[10], res[3].depth(), 3, 1, 0, BORDER_DEFAULT);
    convertScaleAbs(res[10], res[10]);
    imshow("Laplace算子边缘检测", res[10]);
    imwrite("D:\trashBox\testIMG\laplace.jpg", res[10]);
}

//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[3], CV_BGR2GRAY);//转灰度图像
    imshow("灰度图", res[3]);
    equalizeHist(res[3], res[11]);
    imshow("直方图均衡化", res[11]);
    imwrite("D:\trashBox\equalHist.jpg", res[11]); 
}

//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=0; i<3; i++)
            (*itout)[i] = (*it)[i] / div * div + div / 2;//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 <= 0)
    {
        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 0;
    }
    namedWindow("原图像");
    namedWindow("显示结果");

    slider = 0;
    createTrackbar("ColorReduce", "显示结果", &slider, slider_max, on_trackbar);

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

    waitKey(0);
}