opencv再学习之路（二）---滤波算法

#include"stdafx.h"
#include<opencv2opencv.hpp>
#include<opencv2highguihighgui.hpp>
#include<iostream>
#include<Windows.h>
#include<time.h>

using namespace std;
using namespace cv;

// 常见数据结构使用方法
int main()
{
    Mat sourceimage = imread("1.jpg");

    //  线性滤波：均值滤波  方框滤波

    Mat image1;
    long starttime1 = GetTickCount();
    blur(sourceimage,image1,Size(5,5));
    namedWindow("均值滤波",WINDOW_NORMAL);
    imshow("均值滤波",image1);
    long endtime1 = GetTickCount();
    cout << "均值滤波时间：" << (endtime1 - starttime1) << endl;

    Mat image2;
    long starttime2 = GetTickCount();
    boxFilter(sourceimage,image2,-1,Size(5,5));  // 参数 -1 代表采用原图深度
    namedWindow("方框滤波",WINDOW_NORMAL);
    imshow("方框滤波",image2);
    long endtime2 = GetTickCount();
    cout << "方框滤波时间：" << (endtime2 - starttime2) << endl;

    //  非线性滤波： 高斯滤波  双边滤波  中值滤波

    Mat image3;
    long starttime3 = GetTickCount();
    GaussianBlur(sourceimage,image3,Size(3,3),0,0);  // 0，0 为参数 sigx 和 sigy 的值
    namedWindow("高斯滤波",WINDOW_NORMAL);
    imshow("高斯滤波",image3);
    long endtime3 = GetTickCount();
    cout << "高斯滤波时间：" << (endtime3 - starttime3) << endl;

    Mat image4;
    long starttime4 = GetTickCount();
    bilateralFilter(sourceimage,image4,25,25*2,35/2);
    namedWindow("双边滤波",WINDOW_NORMAL);
    imshow("双边滤波",image4);
    long endtime4 = GetTickCount();
    cout << "双边滤波时间：" << (endtime4 - starttime4) << endl;

    Mat image5;
    long starttime5 = GetTickCount();
    medianBlur(sourceimage,image5,5);
    namedWindow("中值滤波",WINDOW_NORMAL);
    imshow("中值滤波",image5);
    long endtime5 = GetTickCount();
    cout << "中值滤波时间：" << (endtime5 - starttime5) << endl;

    waitKey(0);
    return 0;

}

自定义滤波模板：

　　

void main()
{
    Mat srcImage =imread("01.jpg");

    // 基于拉普拉斯算子的图像锐化
    // 拉普拉斯滤波核 3*3
    // 0 -1  0
    //-1  5 -1
    // 0 -1  0
    Mat kernel = (Mat_<float>(3,3) << 0, -1, 0, -1, 5, -1, 0, -1, 0);
    Mat sharpen_laplace;
    filter2D(srcImage, sharpen_laplace, srcImage.depth(), kernel);

    imshow("show", sharpen_laplace);

    waitKey(0);
}