图像预处理五种滤波

【核心代码】

// 图像预处理五种滤波.cpp : 定义控制台应用程序的入口点。
//

#include "stdafx.h"



#include <opencv2/core/core.hpp>

#include <opencv2/highgui/highgui.hpp>

#include <opencv2/imgproc/imgproc.hpp>

#include <iostream>



using namespace cv;

using namespace std;



Mat g_srcImage, g_dstImage1, g_dstImage2, g_dstImage3, g_dstImage4, g_dstImage5;



int g_nBoxFilterValue = 6;		//方框滤波的内核值

int g_nMeanBlurValue = 10;		//均值滤波的内核值

int g_nGaussianBlurValue = 6;	//高斯滤波内核值

int g_nMedianBlurBlurValue = 10;	//中值滤波参数

int g_nBilateralFiterValue = 50;	//双边滤波参数值



									//声明滚动条回调函数

static void on_BoxFilter(int, void*);	//方框

static void on_MeanBulr(int, void*);	//均值

static void on_GaussianBulr(int, void*);	//高斯

static void on_MedianBlur(int, void*);	//中值

static void on_BilateralFiter(int, void*);	//双边



int main()

{

	g_srcImage = imread("C:/Users/nemo/Desktop/2.jpg");

	if (!g_srcImage.data)

	{

		printf("图片载入失败!\n");

		return -1;

	}



	g_dstImage1 = g_srcImage.clone();

	g_dstImage2 = g_srcImage.clone();

	g_dstImage3 = g_srcImage.clone();

	g_dstImage4 = g_srcImage.clone();

	g_dstImage5 = g_srcImage.clone();



	//显示原图

	namedWindow("原图");

	imshow("原图", g_srcImage);



	//方框滤波

	namedWindow("方框滤波");

	//创建滚动条

	createTrackbar("内核值:", "方框滤波", &g_nBoxFilterValue, 50, on_BoxFilter);

	on_BoxFilter(g_nBoxFilterValue, 0);

	imshow("方框滤波", g_dstImage1);



	//均值滤波

	namedWindow("均值滤波");

	createTrackbar("内核值:", "均值滤波", &g_nMeanBlurValue, 50, on_MeanBulr);

	on_MeanBulr(g_nMeanBlurValue, 0);

	imshow("均值滤波", g_dstImage2);



	//高斯

	namedWindow("高斯滤波");

	createTrackbar("内核值:", "高斯滤波", &g_nGaussianBlurValue, 50, on_GaussianBulr);

	on_GaussianBulr(g_nGaussianBlurValue, 0);

	imshow("高斯滤波", g_dstImage3);



	//中值

	namedWindow("中值滤波");

	createTrackbar("内核值:", "中值滤波", &g_nMedianBlurBlurValue, 50, on_MedianBlur);

	on_MedianBlur(g_nMedianBlurBlurValue, 0);

	imshow("中值滤波", g_dstImage4);



	//双边

	namedWindow("双边滤波");

	createTrackbar("内核值:", "双边滤波", &g_nBilateralFiterValue, 50, on_BilateralFiter);

	on_BilateralFiter(g_nBilateralFiterValue, 0);

	imshow("双边滤波", g_dstImage5);



	waitKey(0);

	return 0;

}



//回调函数



//方框

static void on_BoxFilter(int, void*)

{

	//方框滤波操作

	boxFilter(g_srcImage, g_dstImage1, -1, Size(g_nBoxFilterValue   1, g_nBoxFilterValue   1));

	//显示

	imshow("方框滤波", g_dstImage1);

}



//均值

static void on_MeanBulr(int, void*)

{

	blur(g_srcImage, g_dstImage2, Size(g_nMeanBlurValue   1, g_nMeanBlurValue   1));

	imshow("均值滤波", g_dstImage2);

}



//高斯

static void on_GaussianBulr(int, void*)

{

	GaussianBlur(g_srcImage, g_dstImage3, Size(g_nGaussianBlurValue * 2   1, g_nGaussianBlurValue * 2   1), 0, 0);	//大于1的奇数

	imshow("高斯滤波", g_dstImage3);

}



//中值

static void on_MedianBlur(int, void*)

{

	medianBlur(g_srcImage, g_dstImage4, g_nMedianBlurBlurValue * 2   1);

	imshow("中值滤波", g_dstImage4);

}



//双边

static void on_BilateralFiter(int, void*)

{

	bilateralFilter(g_srcImage, g_dstImage5, g_nBilateralFiterValue, g_nBilateralFiterValue * 2, g_nBilateralFiterValue / 2);

	imshow("双边滤波", g_dstImage5);

}