《学习OpenCV》练习题第五章第二题abc

代码：

 #include <stdio.h>
 #include <opencv/highgui.h>
 #include <opencv/cv.h>
 #include <opencv_libs.h>

 /*
  *《学习OpenCV》第五章第二题
  * 完成时间：21:43 10/13 星期日 2013
  * 作者：qdsclove@163.com
  */

 /* Image Size */
 #define   IMG_SIZE   100

 /*
  * Window Title
  */
 #define   WNDTITLE_IMAGE   "source image"
 #define   WNDTITLE_FIVE    "5*5 Gaussian"
 #define   WNDTITLE_NINE    "9*9 Gaussian"
 #define   WNDTITLE_FIVE_TEICE   "5*5 Gaussian Twice"

 /*
  * function: calculate MSE & PSNR of two GrayScale(8-bit depth & one channel) images.
  * param: img1 -- the first image.
  * param: img2 -- the second image.
  * param: dMSE -- the MSE of two images(output)
  * param: dPSNR -- the PSNR of two images(output)
  * return: 0 -- success;  others -- failed.
  */
 int calculateGrayImgsPSNR(IplImage* img1, IplImage* img2, double& dMSE, double& dPSNR)
 {
     if( !img1 || !img2 ||
         img1->nChannels !=  ||
         img2->nChannels !=  ||
         img1->depth != img2->depth ||
         img1->width != img2->width ||
         img1->height != img2->height )
     {
         return -;
     }
     int width = img1->width;
     int height = img1->height;

     // calculate MSE of the two images
     double dSumOfSquares = ;
     for(int i = ; i < height; i++)
     {
         char* pdata1 = img1->imageData + i * img1->widthStep;
         char* pdata2 = img2->imageData + i *img2->widthStep;
         for(int j = ; j < width; j++ )
         {
             uchar value1 = *(pdata1 + j);
             uchar value2 = *(pdata2 + j);

             double square = pow( (double)(value1 - value2),  );
             dSumOfSquares += square;
         }
     }

     dMSE = dSumOfSquares / (width * height);

     // this is means the two images are strictly same.
     if(dMSE == )
     {
         dPSNR = -;
         return ;
     }
     int iDepth = img1->depth;
     int iMAX = pow( ., iDepth) - ;

     dPSNR =  * log10(iMAX / (sqrt(dMSE)));

     return ;
 }

 int main()
 {
     IplImage* image = cvCreateImage( cvSize(IMG_SIZE, IMG_SIZE), IPL_DEPTH_8U,  );
     IplImage* dst_five_gaussian = cvCreateImage( cvGetSize(image), image->depth, image->nChannels );
     IplImage* dst_nine_gaussian = cvCreateImage( cvGetSize(image), image->depth, image->nChannels );
     IplImage* dst_twice_five_gaussian = cvCreateImage(  cvGetSize(image), image->depth, image->nChannels );

     // 全部像素置零
     cvZero(image);
     // 设置中心像素为255
     cvSet2D(image, IMG_SIZE/, IMG_SIZE/, cvScalarAll());

     // 5*5 高斯滤波
     cvSmooth(image, dst_five_gaussian, CV_GAUSSIAN, , );
     // 9*9 高斯滤波
     cvSmooth(image, dst_nine_gaussian, CV_GAUSSIAN, , );
     // 5*5高斯滤波 第二次
     cvSmooth(dst_five_gaussian, dst_twice_five_gaussian, , );

     cvNamedWindow(WNDTITLE_IMAGE, CV_WINDOW_NORMAL);
     cvNamedWindow(WNDTITLE_FIVE, CV_WINDOW_NORMAL);
     cvNamedWindow(WNDTITLE_NINE, CV_WINDOW_NORMAL);
     cvNamedWindow(WNDTITLE_FIVE_TEICE, CV_WINDOW_NORMAL);

     cvShowImage(WNDTITLE_IMAGE, image);
     cvShowImage(WNDTITLE_FIVE, dst_five_gaussian);
     cvShowImage(WNDTITLE_NINE, dst_nine_gaussian);
     cvShowImage(WNDTITLE_FIVE_TEICE, dst_twice_five_gaussian);

     cvSaveImage("source.bmp", image);
     cvSaveImage("5_5_gaussian.bmp", dst_five_gaussian);
     cvSaveImage("9_9_gaussian.bmp", dst_nine_gaussian);
     cvSaveImage("5_5_gaussian_twice.bmp", dst_twice_five_gaussian);

     // c part
     double dMSE = , dPSNR = ;
     calculateGrayImgsPSNR(dst_nine_gaussian, dst_twice_five_gaussian, dMSE, dPSNR);
     printf("9*9 GAUSSIAN & 5*5 GAUSSIAN Twice: MSE: %f\tPSNR: %f\n", dMSE, dPSNR);

     cvWaitKey();

     cvReleaseImage(&image);
     cvReleaseImage(&dst_five_gaussian);
     cvReleaseImage(&dst_nine_gaussian);
     cvDestroyAllWindows();

     return ;
 }

结果分析，这里的截图都是结果图像放大之后的结果：

原图 & 5*5高斯滤波后的图像：

原图 & 5*5高斯滤波后的图像 & 9*9高斯滤波后的图像：

c部分：

原图 & 5*5高斯滤波后的图像 & 9*9高斯滤波后的图像 & 两次5*5高斯滤波后的图像：

9*9平滑一次与5*5平滑两次的MSE与PSNR：

从上一篇博文（http://www.cnblogs.com/qdsclove/p/3366907.html）可知这两幅图像的相似度很高。