openCV学习笔记（二十） —— 图像滤波 —— 线性滤波（方框滤波、均值滤波、高斯滤波）

图像滤波简介

方框滤波——boxFilter（） 

原理

方框滤波程序 

#include
#include 
#include 

using namespace std;
using namespace cv;

#define BOX_FILTER_ORIGINAL_WINDOW_NAME	"方框滤波【原图】"
#define BOX_FILTER_RESULT_WINDOW_NAME	"方框滤波【效果图】"

int main()
{
	//载入原图
	Mat image = imread("test.jpg");

	//创建窗口
	namedWindow(BOX_FILTER_ORIGINAL_WINDOW_NAME);
	namedWindow(BOX_FILTER_RESULT_WINDOW_NAME);

	//显示原图
	imshow(BOX_FILTER_ORIGINAL_WINDOW_NAME, image);

	//进行滤波操作
	Mat out;
	boxFilter(image, out, -1, Size(5, 5));

	//显示效果图
	imshow(BOX_FILTER_RESULT_WINDOW_NAME, out);

	waitKey(0);

	return 0;
}

均值滤波 —— blur（）

原理

 

 均值滤波程序

#include
#include 
#include 

using namespace std;
using namespace cv;

#define BOX_FILTER_ORIGINAL_WINDOW_NAME	"均值滤波【原图】"
#define BOX_FILTER_RESULT_WINDOW_NAME	"均值滤波【效果图】"

int main()
{
	//载入原图
	Mat image = imread("test.jpg");

	//创建窗口
	namedWindow(BOX_FILTER_ORIGINAL_WINDOW_NAME);
	namedWindow(BOX_FILTER_RESULT_WINDOW_NAME);

	//显示原图
	imshow(BOX_FILTER_ORIGINAL_WINDOW_NAME, image);

	//进行滤波操作
	Mat out;
	blur(image, out, Size(5, 5));

	//显示效果图
	imshow(BOX_FILTER_RESULT_WINDOW_NAME, out);

	waitKey(0);

	return 0;
}

高斯滤波——GaussianBlur（）

原理

 

高斯滤波程序 

#include
#include 
#include 

using namespace std;
using namespace cv;

#define BOX_FILTER_ORIGINAL_WINDOW_NAME	"高斯滤波【原图】"
#define BOX_FILTER_RESULT_WINDOW_NAME	"高斯滤波【效果图】"

int main()
{
	//载入原图
	Mat image = imread("test.jpg");

	//创建窗口
	namedWindow(BOX_FILTER_ORIGINAL_WINDOW_NAME);
	namedWindow(BOX_FILTER_RESULT_WINDOW_NAME);

	//显示原图
	imshow(BOX_FILTER_ORIGINAL_WINDOW_NAME, image);

	//进行滤波操作
	Mat out;
	GaussianBlur(image, out, Size(5, 5), 0, 0);

	//显示效果图
	imshow(BOX_FILTER_RESULT_WINDOW_NAME, out);

	waitKey(0);

	return 0;
}

图像线性滤波综合示例程序

 

#include 
#include 

using namespace std;
using namespace cv;

#define BOX_FILTER_WINDOW	"方框滤波"
#define MEAN_BLUR_WINDOW	"均值滤波"
#define GAUSSIAN_BLUR_WINDOW	"高斯滤波"

Mat g_srcImage, g_dstImage1, g_dstImage2, g_dstImage3;	//存储图片的Mat类型
int g_nBoxFilterValue = 3;	//方框滤波参数值
int g_nMeanBlurValue = 3;	//均值滤波参数值
int g_nGaussianBlurValue = 3;	//高斯滤波参数值

//轨迹条的回调函数
static void on_BoxFilter(int, void *);	//方框滤波
static void on_MeanBlur(int, void *);	//均值滤波
static void on_GaussianBlur(int, void *);	//高斯滤波

int main()
{
	//改变console字体颜色
	system("color5E");

	//载入原图
	g_srcImage = imread("test.jpg");
	if (!g_srcImage.data)
	{
		printf("读取srcImage错误！\n");
		return -1;
	}

	//复制原图到三个Mat类型中
	g_dstImage1 = g_srcImage.clone();
	g_dstImage2 = g_srcImage.clone();
	g_dstImage3 = g_srcImage.clone();

	//显示原图
	imshow("原图窗口", g_srcImage);

	//1.方框滤波
	//创建窗口
	namedWindow(BOX_FILTER_WINDOW);
	//创建轨迹条
	createTrackbar("内核值：", BOX_FILTER_WINDOW, &g_nBoxFilterValue, 40, on_BoxFilter);
	on_BoxFilter(g_nBoxFilterValue, 0);
	imshow(BOX_FILTER_WINDOW, g_dstImage1);

	//2.均值滤波
	//创建窗口
	namedWindow(MEAN_BLUR_WINDOW);
	//创建轨迹条
	createTrackbar("内核值：", MEAN_BLUR_WINDOW, &g_nMeanBlurValue, 40, on_MeanBlur);
	on_MeanBlur(g_nMeanBlurValue, 0);

	//3.高斯滤波
	//创建窗口
	namedWindow(GAUSSIAN_BLUR_WINDOW);
	createTrackbar("内核值：", GAUSSIAN_BLUR_WINDOW, &g_nGaussianBlurValue, 40, on_GaussianBlur);
	on_GaussianBlur(g_nGaussianBlurValue, 0);

	//输出一些帮助信息
	cout << endl << "\t请调整滚动条观察图像效果\n"
		<< "\t按下“q”键时，程序退出!\n";

	//按下"q"键时，程序退出
	while (char(waitKey(1)) != 'q');
	destroyAllWindows();

	return 0;
}

static void on_BoxFilter(int, void *)
{
	boxFilter(g_srcImage, g_dstImage1, -1, Size(g_nBoxFilterValue + 1, g_nBoxFilterValue + 1));
	imshow("方框滤波", g_dstImage1);
}

static void on_MeanBlur(int, void *)
{
	blur(g_srcImage, g_dstImage2, Size(g_nMeanBlurValue + 1, g_nMeanBlurValue + 1), Point(-1, -1));
	imshow("均值滤波", g_dstImage2);
}

static void on_GaussianBlur(int, void *)
{
	GaussianBlur(g_srcImage, g_dstImage3, Size(g_nGaussianBlurValue*2 + 1, g_nGaussianBlurValue*2 + 1), 0, 0);
	imshow("高斯滤波", g_dstImage3);
}