线性滤波

 

一、方框滤波

1 void boxFilter( InputArray src, OutputArray dst, int ddepth,
2                              Size ksize, Point anchor = Point(-1,-1),
3                              bool normalize = true,
4                              int borderType = BORDER_DEFAULT );

二、均值滤波

 

1 void blur( InputArray src, OutputArray dst,
2                         Size ksize, Point anchor = Point(-1,-1),
3                         int borderType = BORDER_DEFAULT );

 

 

三、高斯滤波

1 void GaussianBlur( InputArray src, OutputArray dst, Size ksize,
2                                 double sigmaX, double sigmaY = 0,
3                                 int borderType = BORDER_DEFAULT );

 

 

 1 #include<opencv2/opencv.hpp>
 2 #include<iostream>
 3 
 4 using namespace std;
 5 using namespace cv;
 6 
 7 Mat g_srcImage, g_dstImage1, g_dstImage2, g_dstImage3;
 8 int g_nBoxFilterValue = 3;  //方框滤波参数值
 9 int g_nMeanBlurValue = 3;   //均值滤波参数值
10 int g_nGaussianBlurValue = 3;  //高斯滤波参数值
11 
12 static void on_BoxFilter(int, void *);   //方框滤波
13 static void on_MeanBlur(int, void *);   //均值滤波
14 static void on_GaussianBlur(int, void *);  //高斯滤波
15 
16 int main() {
17     //改变console字体颜色
18     system("color 5E");
19 
20     //载入原图
21     g_srcImage = imread("C:\\Users\\Administrator\\Pictures\\Camera Roll\\05.jpg");
22     if (!g_srcImage.data) {
23         printf("读取srcIamge错误！\n");
24         return false;
25     }
26 
27     //复制原图到三个Mat类型中
28     g_dstImage1 = g_srcImage.clone();
29     g_dstImage2 = g_srcImage.clone();
30     g_dstImage3 = g_srcImage.clone();
31 
32     //显示原图
33     namedWindow("【原图窗口】", 1);
34     imshow("【原图窗口】", g_srcImage);
35 
36     //=====【方框滤波】======
37     //创建窗口
38     namedWindow("【方框滤波】",1);
39     //创建轨迹条
40     createTrackbar("内核值：", "【方框滤波】", &g_nBoxFilterValue, 40, on_BoxFilter);
41     on_BoxFilter(g_nBoxFilterValue, 0);
42     
43 
44     //=====【均值滤波】======
45     //创建窗口
46     namedWindow("【均值滤波】", 1);
47     //创建轨迹条
48     createTrackbar("内核值：", "【均值滤波】", &g_nMeanBlurValue, 40, on_MeanBlur);
49     on_MeanBlur(g_nMeanBlurValue, 0);
50     
51 
52     //=====【高斯滤波】======
53     //创建窗口
54     namedWindow("【高斯滤波】", 1);
55     //创建轨迹条
56     createTrackbar("内核值：", "【高斯滤波】", &g_nGaussianBlurValue, 40, on_GaussianBlur);
57     on_GaussianBlur(g_nGaussianBlurValue, 0);
58 
59     while (char(waitKey(1) != 'q')) {}
60     
61     return 0;
62 }
63 
64 static void on_BoxFilter(int, void *) {   //方框滤波
65     //方框滤波操作
66     boxFilter(g_srcImage, g_dstImage1, -1, Size(g_nBoxFilterValue + 1, g_nBoxFilterValue + 1));
67     //显示窗口
68     imshow("【方框滤波】", g_dstImage1);
69 }
70 static void on_MeanBlur(int, void *) {   //均值滤波
71     //均值滤波操作
72     blur(g_srcImage, g_dstImage2, Size(g_nMeanBlurValue + 1, g_nMeanBlurValue + 1), Point(-1, -1));
73     //显示窗口
74     imshow("【均值滤波】", g_dstImage2);
75 }
76 static void on_GaussianBlur(int, void *) {  //高斯滤波
77     //高斯滤波操作
78     GaussianBlur(g_srcImage, g_dstImage3, Size(g_nGaussianBlurValue * 2 + 1, g_nGaussianBlurValue * 2 + 1), 0, 0);
79     //显示窗口
80     imshow("【高斯滤波】", g_dstImage3);
81 }

 

转载于:https://www.cnblogs.com/Nelsoner/p/6776232.html