int main()
 {
	 IplImage* img = cvLoadImage("C:\\vvv.jpg", 0);

     IplImage *avgImg = cvCreateImage(cvGetSize(img), IPL_DEPTH_8U, img->nChannels);   
	 IplImage *medianImg = cvCreateImage(cvGetSize(img), IPL_DEPTH_8U, img->nChannels); 
	 IplImage *gaussianImg = cvCreateImage(cvGetSize(img), IPL_DEPTH_8U, img->nChannels); 


	 cvSmooth(img, avgImg, CV_BLUR, 7,img->nChannels);  //采用7x7的窗口对图像进行均值滤波  

	 cvSmooth(img, medianImg, CV_MEDIAN, 7, img->nChannels);  //采用7x7的窗口对图像进行中值滤波  

	 cvSmooth(img, gaussianImg, CV_GAUSSIAN, 7, img->nChannels);  //  Gauss平滑滤波,核大小为7x7 
												//高斯的核不同于上面两个,它实现了领域像素的加权平均,离中心越近的像素权重越高
	 cvShowManyImages("result", 3, avgImg, medianImg, gaussianImg);

	 cvWaitKey(-1);

	 return 0;
 }

http://blog.csdn.net/timidsmile/article/details/17289533