OpenCv，椒盐噪声，经典邻域处理，及其在MFC下的实现

<pre name="code" class="html">/*
*开发环境：Win7,32位系统，VS2012,Win32 Console Application程序
*OpenCv版本：2.4.9
*程序功能：生成椒盐噪声，多种方式去噪
*日期：2014/12/2
*原创：是
*作者：EbowTang
*Email：[email protected]
*/
// ConsoleAppOpenCvMedian.cpp : 定义控制台应用程序的入口点。
//

#include "stdafx.h"
#include <opencv2/core/core.hpp>//cv::Mat是一个n维矩阵类
#include <opencv2/highgui/highgui.hpp>//提供输入输出接口
#include <opencv2/imgproc/imgproc.hpp>//图像处理
#include <time.h>
#include "iostream"

using namespace cv;
using namespace std;

void ColorSalt(Mat& image, int n)//本函数加入彩色盐噪声
{
	srand( (unsigned)time( NULL ) );
	for(int k=0; k<n; k++)//将图像中n个像素随机置零
	{
		int i = rand()%image.cols;
		int j = rand()%image.rows;
		//将图像颜色随机改变
		image.at<Vec3b>(j,i)[0] = 250;
		image.at<Vec3b>(j,i)[1] = 150;
		image.at<Vec3b>(j,i)[2] = 250;
	}
}

void ColorPepper(Mat& image, int n)//本函数加入彩色椒噪声
{
	srand( (unsigned)time( NULL ) );
	for(int k=0; k<n; k++)
	{
		int i = rand()%image.cols;
		int j = rand()%image.rows;
		//将图像颜色随机改变
		image.at<Vec3b>(j,i)[0] = 250;
		image.at<Vec3b>(j,i)[1] = 150;
		image.at<Vec3b>(j,i)[2] = 50;
	}
}

int main()
{
	//源图像
	Mat scr = imread("lena.bmp");
	Mat dst;
	Mat img = scr.clone();
	Mat img1 = scr.clone();

	cout<<scr.channels()<<" "<<scr.type()<<"  "<<scr.depth();
	imshow("原图像",scr);
	
	Mat sobelx;
	Sobel(scr, sobelx, CV_32F, 1, 0);
	imshow("Sobel的结果",sobelx);

	ColorSalt(scr, 5000);  //加入白盐噪声
	ColorPepper(scr, 1000); //加入黑椒噪声
	imshow("带噪声的图像",scr);
	medianBlur(scr,dst,3);	//中值滤波，3*3模板内排序并求中值取代原像素
	imshow("中值滤波结果",dst);

	ColorSalt(img, 5000);
	ColorPepper(img, 1000); 
	blur(img,dst,Size(3,3));//均值滤波，3*3模板内求取中间值取代原像素
	imshow("均值滤波结果",dst);

	ColorSalt(img1, 5000);
	ColorPepper(img1, 1000); 
	GaussianBlur( img1, dst, Size( 3, 3 ), 0, 0 );//高斯滤波,
	imshow("高斯滤波结果",dst);

	Rect r( 0, 0, 100, 100);
	//img = Scalar(50);//将图像img的像素赋值为50
	Mat smallImg = img(r);//截取显示img图像中形状为r的部分图像
	imshow("截图显示结果",smallImg);

	waitKey(NULL);//无限等待
	return EXIT_SUCCESS;
}

去噪效果如下：

为什么256级的灰度图是3个通道...？灰度图不应该是1么？

二，OpenCv+MFC实现

1，部分函数

<pre name="code" class="cpp">void CMFCAppOpenCVTestDlg::OnBnClickedBtnRead()
{
	// TODO: Add your control notification handler code here
	m_cvImg = imread("Oct.bmp", 1);
	ShowImg(GetDlgItem(IDC_STATIC_SHOW), m_cvImg);
}

void CMFCAppOpenCVTestDlg::OnBnClickedBtnMedian()
{
	// TODO: Add your control notification handler code here
	Mat m_cvDst = m_cvImg.clone(); 
	medianBlur(m_cvImg,m_cvDst,3);  //中值滤波，3*3模板内排序并求中值取代原像素 
	ShowImg(GetDlgItem(IDC_STATIC_SHOW), m_cvDst);
}

void CMFCAppOpenCVTestDlg::OnBnClickedBtnAddnoise()
{
	// TODO: Add your control notification handler code here
	SaltNoise(m_cvImg,5000);
	ShowImg(GetDlgItem(IDC_STATIC_SHOW), m_cvImg);
}

void CMFCAppOpenCVTestDlg::SaltNoise(Mat& image, int n)
{
	srand( (unsigned)time( NULL ) );  
	srand( (unsigned)time( NULL ) );  
	if (image.channels()==3)
	{
		for(int k=0; k<n; k++)//将图像中n个像素随机置零  
		{  
			int i = rand()%image.cols;  
			int j = rand()%image.rows;  
			//将图像颜色随机改变  
			image.at<Vec3b>(j,i)[0] = 250;  
			image.at<Vec3b>(j,i)[1] = 150;  
			image.at<Vec3b>(j,i)[2] = 250;  
		}  
	}
	else
	{
		for(int k=0; k<n; k++)//将图像中n个像素随机置零  
		{  
			int i = rand()%image.cols;  
			int j = rand()%image.rows;  
			//将图像颜色随机改变  
			image.at<uchar>(j,i) = 250;  
		}  
	}
}

void CMFCAppOpenCVTestDlg::OnBnClickedBtnBlur()
{
	// TODO: Add your control notification handler code here
	Mat m_cvDst1 = m_cvImg.clone(); 
	blur(m_cvImg,m_cvDst1,Size(3,3));  //中值滤波，3*3模板内排序并求中值取代原像素 
	ShowImg(GetDlgItem(IDC_STATIC_SHOW), m_cvDst1);
}

void CMFCAppOpenCVTestDlg::OnBnClickedBtnGaussianblur()
{
	// TODO: Add your control notification handler code here
	Mat m_cvDst2 = m_cvImg.clone(); 
	GaussianBlur(m_cvImg,m_cvDst2,Size(3,3),0,0);  //中值滤波，3*3模板内排序并求中值取代原像素 
	ShowImg(GetDlgItem(IDC_STATIC_SHOW), m_cvDst2);
}

2，运行效果如下：