几种典型的立体匹配算法

使用左右两张图片，计算深度图。一下几种算法代码参考 
http://www.360doc.com/content/13/0129/11/11533449_263014896.shtml，经验证可行。并得到一下的深度图，貌似DP算法比较快并且效果还蛮好的。

SAD算法

#include<iostream>   #include<cv.h>   #include<highgui.h>   using namespace std;  int GetHammingWeight(unsigned int value);  int main(){      /*Half of the window size for the census transform*/      int hWin = 11;      int compareLength = (2*hWin+1)*(2*hWin+1);      cout<<"hWin: "<<hWin<<";  "<<"compare length:  "<<compareLength<<endl;        cout<<"SAD test"<<endl;      // char stopKey;       IplImage * leftImage = cvLoadImage("left.bmp",0);      IplImage * rightImage = cvLoadImage("right.bmp",0);      int imageWidth = leftImage->width;      int imageHeight =leftImage->height;      IplImage * SADImage = cvCreateImage(cvGetSize(leftImage),leftImage->depth,1);      IplImage * MatchLevelImage = cvCreateImage(cvGetSize(leftImage),leftImage->depth,1);      int minDBounds = 0;      int maxDBounds = 31;      cvNamedWindow("Left",1);      cvNamedWindow("Right",1);      cvNamedWindow("Census",1);      cvNamedWindow("MatchLevel",1);      cvShowImage("Left",leftImage);      cvShowImage("Right",rightImage);      /*Census Transform */      int i,j ,m,n,k;      unsigned char centerPixel = 0;       unsigned char neighborPixel = 0;      int bitCount = 0;      unsigned int bigger = 0;      int sum = 0;      unsigned int *matchLevel = new unsigned int[maxDBounds - minDBounds  + 1];      int tempMin = 0;      int tempIndex = 0;      unsigned char* dst;      unsigned char* leftSrc  = NULL;      unsigned char* rightSrc = NULL;      unsigned char leftPixel = 0;      unsigned char rightPixel =0;      unsigned char subPixel = 0;      for(i = 0 ; i < leftImage->height;i++){          for(j = 0; j< leftImage->width;j++){              for (k = minDBounds;k <= maxDBounds;k++)              {                  sum = 0;                  for (m = i-hWin; m <= i + hWin;m++)                  {                      for (n = j - hWin; n <= j + hWin;n++)                      {                            if (m < 0 || m >= imageHeight || n <0 || n >= imageWidth )                            {                                subPixel  = 0;                            }else if (n + k >= imageWidth)                            {                                subPixel = 0;                            }else                            {                                leftSrc = (unsigned char*)leftImage->imageData                                             + m*leftImage->widthStep + n + k;                                 rightSrc = (unsigned char*)rightImage->imageData                                              + m*rightImage->widthStep + n;                                leftPixel = *leftSrc;                                rightPixel = *rightSrc;                                if (leftPixel > rightPixel)                                {                                     subPixel = leftPixel - rightPixel;                                }else                                 {                                     subPixel = rightPixel -leftPixel;                                }                            }                            sum += subPixel;                      }                  }                  matchLevel[k] = sum;                  //cout<<sum<<endl;               }              /*寻找最佳匹配点*/             // matchLevel[0] = 1000000;               tempMin = 0;              tempIndex = 0;              for ( m = 1;m < maxDBounds - minDBounds + 1;m++)              {                  //cout<<matchLevel[m]<<endl;                   if (matchLevel[m] < matchLevel[tempIndex])                  {                      tempMin = matchLevel[m];                      tempIndex = m;                  }              }              dst = (unsigned char *)SADImage->imageData + i*SADImage->widthStep + j;              //cout<<"index: "<<tempIndex<<"  ";               *dst = tempIndex*8;              dst = (unsigned char *)MatchLevelImage->imageData + i*MatchLevelImage->widthStep + j;              *dst = tempMin;              //cout<<"min:  "<<tempMin<<"  ";               //cout<< tempIndex<<"  " <<tempMin<<endl;           }          //cvWaitKey(0);       }      cvShowImage("Census",SADImage);      cvShowImage("MatchLevel",MatchLevelImage);      cvSaveImage("depth.jpg",SADImage);      cvSaveImage("matchLevel.jpg",MatchLevelImage);      cvWaitKey(0);      cvDestroyAllWindows();      cvReleaseImage(&leftImage);      cvReleaseImage(&rightImage);      return 0;  }  
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SSD算法：

#include<iostream>   #include<cv.h>   #include<highgui.h>   using namespace std;  int GetHammingWeight(unsigned int value);  int main(){      /*Half of the window size for the census transform*/      int hWin = 11;      int compareLength = (2*hWin+1)*(2*hWin+1);      cout<<"hWin: "<<hWin<<";  "<<"compare length:  "<<compareLength<<endl;        cout<<"SAD test"<<endl;      // char stopKey;       IplImage * leftImage = cvLoadImage("l2.jpg",0);      IplImage * rightImage = cvLoadImage("r2.jpg",0);      int imageWidth = leftImage->width;      int imageHeight =leftImage->height;      IplImage * SADImage = cvCreateImage(cvGetSize(leftImage),leftImage->depth,1);      IplImage * MatchLevelImage = cvCreateImage(cvGetSize(leftImage),leftImage->depth,1);      int minDBounds = 0;      int maxDBounds = 31;      cvNamedWindow("Left",1);      cvNamedWindow("Right",1);      cvNamedWindow("Census",1);      cvNamedWindow("MatchLevel",1);      cvShowImage("Left",leftImage);      cvShowImage("Right",rightImage);      /*Census Transform */      int i,j ,m,n,k;      unsigned char centerPixel = 0;       unsigned char neighborPixel = 0;      int bitCount = 0;      unsigned int bigger = 0;      int sum = 0;      unsigned int *matchLevel = new unsigned int[maxDBounds - minDBounds  + 1];      int tempMin = 0;      int tempIndex = 0;      unsigned char* dst;      unsigned char* leftSrc  = NULL;      unsigned char* rightSrc = NULL;      unsigned char leftPixel = 0;      unsigned char rightPixel =0;      unsigned char subPixel = 0;      for(i = 0 ; i < leftImage->height;i++){          for(j = 0; j< leftImage->width;j++){              for (k = minDBounds;k <= maxDBounds;k++)              {                  sum = 0;                  for (m = i-hWin; m <= i + hWin;m++)                  {                      for (n = j - hWin; n <= j + hWin;n++)                      {                            if (m < 0 || m >= imageHeight || n <0 || n >= imageWidth )                            {                                subPixel  = 0;                            }else if (n + k >= imageWidth)                            {                                subPixel = 0;                            }else                            {                                leftSrc = (unsigned char*)leftImage->imageData                                             + m*leftImage->widthStep + n + k;                                 rightSrc = (unsigned char*)rightImage->imageData                                              + m*rightImage->widthStep + n;                                leftPixel = *leftSrc;                                rightPixel = *rightSrc;                                if (leftPixel > rightPixel)                                {                                     subPixel = leftPixel - rightPixel;                                }else                                 {                                     subPixel = rightPixel -leftPixel;                                }                            }                            sum += subPixel*subPixel;                      }                  }                  matchLevel[k] = sum;                  //cout<<sum<<endl;               }              /*寻找最佳匹配点*/             // matchLevel[0] = 1000000;               tempMin = 0;              tempIndex = 0;              for ( m = 1;m < maxDBounds - minDBounds + 1;m++)              {                  //cout<<matchLevel[m]<<endl;                   if (matchLevel[m] < matchLevel[tempIndex])                  {                      tempMin = matchLevel[m];                      tempIndex = m;                  }              }              dst = (unsigned char *)SADImage->imageData + i*SADImage->widthStep + j;              //cout<<"index: "<<tempIndex<<"  ";               *dst = tempIndex*8;              dst = (unsigned char *)MatchLevelImage->imageData + i*MatchLevelImage->widthStep + j;              *dst = tempMin;              //cout<<"min:  "<<tempMin<<"  ";               //cout<< tempIndex<<"  " <<tempMin<<endl;           }          //cvWaitKey(0);       }      cvShowImage("Census",SADImage);      cvShowImage("MatchLevel",MatchLevelImage);      cvSaveImage("depth.jpg",SADImage);      cvSaveImage("matchLevel.jpg",MatchLevelImage);      cvWaitKey(0);      cvDestroyAllWindows();      cvReleaseImage(&leftImage);      cvReleaseImage(&rightImage);      return 0;  }  

ZSSD算法：

#include<iostream>   #include<cv.h>   #include<highgui.h>   using namespace std;  int GetHammingWeight(unsigned int value);  int main(){      /*Half of the window size for the census transform*/      int hWin = 11;      int compareLength = (2*hWin+1)*(2*hWin+1);      cout<<"hWin: "<<hWin<<";  "<<"compare length:  "<<compareLength<<endl;        cout<<"ZSSD test"<<endl;      // char stopKey;     /*  IplImage * leftImage = cvLoadImage("l2.jpg",0);     IplImage * rightImage = cvLoadImage("r2.jpg",0);*/      IplImage * leftImage = cvLoadImage("left.bmp",0);      IplImage * rightImage = cvLoadImage("right.bmp",0);      int imageWidth = leftImage->width;      int imageHeight =leftImage->height;      IplImage * SADImage = cvCreateImage(cvGetSize(leftImage),leftImage->depth,1);      IplImage * MatchLevelImage = cvCreateImage(cvGetSize(leftImage),leftImage->depth,1);      int minDBounds = 0;      int maxDBounds = 31;      cvNamedWindow("Left",1);      cvNamedWindow("Right",1);      cvNamedWindow("Census",1);      cvNamedWindow("MatchLevel",1);      cvShowImage("Left",leftImage);      cvShowImage("Right",rightImage);      /*Census Transform */      int i,j ,m,n,k;      unsigned char centerPixel = 0;       unsigned char neighborPixel = 0;      int bitCount = 0;      unsigned int bigger = 0;      int sumLeft = 0;      int sumRight = 0;      int sum =0;      int zSumLeft  = 0;      int zSumRight = 0;      unsigned int *matchLevel = new unsigned int[maxDBounds - minDBounds  + 1];      int tempMin = 0;      int tempIndex = 0;      unsigned char* dst;      unsigned char* leftSrc  = NULL;      unsigned char* rightSrc = NULL;      unsigned char leftPixel = 0;      unsigned char rightPixel =0;      unsigned char subPixel = 0;      unsigned char meanLeftPixel  = 0;      unsigned char meanRightPixel = 0;      for(i = 0 ; i < leftImage->height;i++){          for(j = 0; j< leftImage->width;j++){              /*均值计算 */              for (k = minDBounds;k <= maxDBounds;k++)              {                  sumLeft  = 0;                  sumRight = 0;                  for (m = i-hWin; m <= i + hWin;m++)                  {                      for (n = j - hWin; n <= j + hWin;n++)                      {                            if (m < 0 || m >= imageHeight || n <0 || n >= imageWidth )                            {                                sumLeft += 0;                            }else {                                leftSrc = (unsigned char*)leftImage->imageData                                     + m*leftImage->widthStep + n + k;                                 leftPixel = *leftSrc;                                sumLeft += leftPixel;                            }                            if (m < 0 || m >= imageHeight || n + k <0 || n +k >= imageWidth)                            {                                 sumRight += 0;                            }else                            {                                 rightSrc = (unsigned char*)rightImage->imageData                                              + m*rightImage->widthStep + n;                                rightPixel = *rightSrc;                                sumRight += rightPixel;                               }                      }                  }                  meanLeftPixel  = sumLeft/compareLength;                  meanRightPixel = sumRight/compareLength;                   /*ZSSD*/                 sum = 0;                   for (m = i-hWin; m <= i + hWin;m++)                  {                      for (n = j - hWin; n <= j + hWin;n++)                      {                            if (m < 0 || m >= imageHeight || n <0 || n >= imageWidth )                            {                                //zSumLeft += 0;                                 leftPixel = 0;                            }else {                                leftSrc = (unsigned char*)leftImage->imageData                                     + m*leftImage->widthStep + n + k;                                 leftPixel = *leftSrc;                                //zSumLeft += (leftPixel - meanLeftPixel)*(leftPixel -meanLeftPixel);                             }                            if (m < 0 || m >= imageHeight || n + k <0 || n +k >= imageWidth)                            {                                 //zSumRight += 0;                                 rightPixel = 0;                            }else                            {                                 rightSrc = (unsigned char*)rightImage->imageData                                              + m*rightImage->widthStep + n;                                rightPixel = *rightSrc;                                // zSumRight += (rightPixel - meanRightPixel)*(rightPixel - meanRightPixel);                                }                            sum += ((rightPixel - meanRightPixel)-(leftPixel -meanLeftPixel))                                   *((rightPixel - meanRightPixel)-(leftPixel -meanLeftPixel));                      }                  }                  matchLevel[k] = sum;                  //cout<<sum<<endl;               }              /*寻找最佳匹配点*/             // matchLevel[0] = 1000000;               tempMin = 0;              tempIndex = 0;              for ( m = 1;m < maxDBounds - minDBounds + 1;m++)              {                  //cout<<matchLevel[m]<<endl;                   if (matchLevel[m] < matchLevel[tempIndex])                  {                      tempMin = matchLevel[m];                      tempIndex = m;                  }              }              dst = (unsigned char *)SADImage->imageData + i*SADImage->widthStep + j;              //cout<<"index: "<<tempIndex<<"  ";               *dst = tempIndex*8;              dst = (unsigned char *)MatchLevelImage->imageData + i*MatchLevelImage->widthStep + j;              *dst = tempMin;              //cout<<"min:  "<<tempMin<<"  ";               //cout<< tempIndex<<"  " <<tempMin<<endl;           }         // cvWaitKey(0);       }      cvShowImage("Census",SADImage);      cvShowImage("MatchLevel",MatchLevelImage);      cvSaveImage("depth.jpg",SADImage);      cvSaveImage("matchLevel.jpg",MatchLevelImage);      cout<<endl<<"Over"<<endl;      cvWaitKey(0);      cvDestroyAllWindows();      cvReleaseImage(&leftImage);      cvReleaseImage(&rightImage);      return 0;  }  
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census 算法：

#include<iostream>   #include<cv.h>   #include<highgui.h>   using namespace std;  int GetHammingWeight(unsigned int value);  int main(){      /*Half of the window size for the census transform*/      int hWin = 11;      int bitlength = 0;      if ((2*hWin+1)*(2*hWin+1)%32 == 0)      {          bitlength = (2*hWin+1)*(2*hWin+1)/32;      }else {          bitlength = (2*hWin+1)*(2*hWin+1)/32  + 1;       }        cout<<"hWin: "<<hWin<<";  "<<"bit length:  "<<bitlength<<endl;        cout<<"Census test"<<endl;     // char stopKey;       IplImage * leftImage = cvLoadImage("left.bmp",0);      IplImage * rightImage = cvLoadImage("right.bmp",0);      int imageWidth = leftImage->width;      int imageHeight =leftImage->height;      IplImage * CensusImage = cvCreateImage(cvGetSize(leftImage),leftImage->depth,1);      IplImage * MatchLevelImage = cvCreateImage(cvGetSize(leftImage),leftImage->depth,1);       int minDBounds = 0;       int maxDBounds = 31;      // int leftCensus[imageHeight][imageWidth][bitlength] = {0};          unsigned  int *leftCensus = new unsigned int[imageHeight*imageWidth*bitlength];       unsigned  int *rightCensus = new unsigned int[imageHeight*imageWidth*bitlength];        for (int i = 0;i < imageHeight*imageWidth*bitlength;i++)       {           leftCensus[i] = 0;           rightCensus[i] = 0;       }       int pointCnt = 0;      cvNamedWindow("Left",1);      cvNamedWindow("Right",1);      cvNamedWindow("Census",1);      cvNamedWindow("MatchLevel",1);      cvShowImage("Left",leftImage);      cvShowImage("Right",rightImage);      /*Census Transform */     int i,j ,m,n,k,l;     unsigned char centerPixel = 0;      unsigned char neighborPixel = 0;     int bitCount = 0;     unsigned int bigger = 0;      for(i = 0 ; i < leftImage->height;i++){          for(j = 0; j< leftImage->width;j++){               centerPixel = *((unsigned char *)leftImage->imageData + i*leftImage->widthStep + j);                bitCount = 0;               for (m = i - hWin; m <= i + hWin;m++)               {                   for (n = j - hWin; n<= j+hWin;n++)                   {                       bitCount++;                       if (m < 0 || m >= leftImage->height || n < 0 || n >= leftImage->width)                       {                           neighborPixel = 0;                       }else{                            neighborPixel = *((unsigned char *)leftImage->imageData + m*leftImage->widthStep + n);                        }                       bigger = (neighborPixel > centerPixel)?1:0;                       leftCensus[(i*imageWidth + j)*bitlength + bitCount/32] |= (bigger<<(bitCount%32));                   }               }          }      }      for(i = 0 ; i < rightImage->height;i++){          for(j = 0; j< rightImage->width;j++){              centerPixel = *((unsigned char *)rightImage->imageData + i*rightImage->widthStep + j);               bitCount = 0;              for (m = i - hWin; m <= i + hWin;m++)              {                  for (n = j - hWin; n<= j+hWin;n++)                  {                      bitCount++;                      if (m < 0 || m >= rightImage->height || n < 0 || n >= rightImage->width)                      {                          neighborPixel = 0;                      }else{                          neighborPixel = *((unsigned char *)rightImage->imageData + m*rightImage->widthStep + n);                       }                      bigger = (neighborPixel > centerPixel)?1:0;                      rightCensus[(i*imageWidth + j)*bitlength + bitCount/32] |= (bigger<<(bitCount%32));                  }              }          }      }      int sum = 0;      unsigned int *matchLevel = new unsigned int[maxDBounds - minDBounds  + 1];      int tempMin = 0;      int tempIndex = 0;      unsigned  char *dst;      unsigned char pixle = 0;      for(i = 0 ; i < rightImage->height;i++){          for(j = 0; j< rightImage->width;j++){              for (k = minDBounds;k <= maxDBounds;k++)              {                  sum = 0;                  for (l = 0;l< bitlength;l++)                  {                         if (((i*imageWidth+j+k)*bitlength + l) < imageHeight*imageWidth*bitlength)                      {                          sum += GetHammingWeight(rightCensus[(i*imageWidth+j)*bitlength + l]                           ^ leftCensus[(i*imageWidth+j+k)*bitlength + l]);                      }else {                          //sum += 0;                          // cout<<".";                       }                  }                  matchLevel[k] = sum;              }              /*寻找最佳匹配点*/              tempMin = 0;              tempIndex = 0;              for ( m = 1;m < maxDBounds - minDBounds + 1;m++)              {                   if (matchLevel[m] < matchLevel[tempIndex])                   {                       tempMin = matchLevel[m];                       tempIndex = m;                   }              }              if (tempMin > (2*hWin+1)*(2*hWin+1)*0.2)              {                  tempMin = 0;                  pointCnt++;              }else{                  tempMin = 255;              }              dst = (unsigned char *)CensusImage->imageData + i*CensusImage->widthStep + j;              *dst = tempIndex*8;              dst = (unsigned char *)MatchLevelImage->imageData + i*MatchLevelImage->widthStep + j;              *dst = tempMin;              //cout<< tempIndex<<"  " <<tempMin<<endl;;           }      }      cout<<"pointCnt:  "<<pointCnt<<endl;      cvShowImage("Census",CensusImage);      cvShowImage("MatchLevel",MatchLevelImage);      cvSaveImage("depth.jpg",CensusImage);      cvSaveImage("matchLevel.jpg",MatchLevelImage);      cvWaitKey(0);      cvDestroyAllWindows();      cvReleaseImage(&leftImage);      cvReleaseImage(&rightImage);      return 0;  }  int GetHammingWeight(unsigned int value)  {      if(value == 0) return 0;      int a = value;      int b = value -1;      int c = 0;      int count = 1;      while(c = a & b)      {          count++;          a = c;          b = c-1;      }      return count;  }  
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NCC算法：

#include<iostream>   #include<cv.h>   #include<highgui.h>   #include <cmath>   using namespace std;  int main(){      /*Half of the window size for the census transform*/      int hWin = 11;      int compareLength = (2*hWin+1)*(2*hWin+1);      cout<<"hWin: "<<hWin<<";  "<<"compare length:  "<<compareLength<<endl;        cout<<"NCC test"<<endl;    /*  IplImage * leftImage = cvLoadImage("l2.jpg",0);     IplImage * rightImage = cvLoadImage("r2.jpg",0);*/      IplImage * leftImage = cvLoadImage("left.bmp",0);                                 IplImage * rightImage = cvLoadImage("right.bmp",0);      int imageWidth = leftImage->width;      int imageHeight =leftImage->height;      IplImage * NCCImage = cvCreateImage(cvGetSize(leftImage),leftImage->depth,1);      IplImage * MatchLevelImage = cvCreateImage(cvGetSize(leftImage),leftImage->depth,1);      int minDBounds = 0;      int maxDBounds = 31;      cvNamedWindow("Left",1);      cvNamedWindow("Right",1);      cvNamedWindow("Census",1);      cvNamedWindow("MatchLevel",1);      cvShowImage("Left",leftImage);      cvShowImage("Right",rightImage);      /*Census Transform */      int i,j ,m,n,k;      unsigned char centerPixel = 0;       unsigned char neighborPixel = 0;      int bitCount = 0;      unsigned int bigger = 0;      unsigned int sum =0;      unsigned int leftSquareSum = 0;      unsigned int rightSquareSum = 0;       double *matchLevel = new double[maxDBounds - minDBounds  + 1];      double tempMax = 0;      int tempIndex = 0;      unsigned char* dst;      unsigned char* leftSrc  = NULL;      unsigned char* rightSrc = NULL;      unsigned char leftPixel = 0;      unsigned char rightPixel =0;      unsigned char subPixel = 0;      unsigned char meanLeftPixel  = 0;      unsigned char meanRightPixel = 0;      for(i = 0 ; i < leftImage->height;i++){          for(j = 0; j< leftImage->width;j++){              /*均值计算 */              for (k = minDBounds;k <= maxDBounds;k++)              {                  sum = 0;                  leftSquareSum  = 0;                  rightSquareSum = 0;                   for (m = i-hWin; m <= i + hWin;m++)                  {                      for (n = j - hWin; n <= j + hWin;n++)                      {                            if (m < 0 || m >= imageHeight || n <0 || n >= imageWidth )                            {                                leftPixel = 0;                            }else {                                leftSrc = (unsigned char*)leftImage->imageData                                     + m*leftImage->widthStep + n + k;                                 leftPixel = *leftSrc;                            }                            if (m < 0 || m >= imageHeight || n + k <0 || n +k >= imageWidth)                            {                                rightPixel = 0;                            }else                            {                                 rightSrc = (unsigned char*)rightImage->imageData                                              + m*rightImage->widthStep + n;                                rightPixel = *rightSrc;                            }                            sum +=  leftPixel*rightPixel;                            leftSquareSum  += leftPixel*leftPixel;                            rightSquareSum += rightPixel*rightPixel;                      }                  }                  matchLevel[k] = (double)sum/(sqrt(double(leftSquareSum))*sqrt((double)rightSquareSum));              }              tempMax = 0;              tempIndex = 0;              for ( m = 1;m < maxDBounds - minDBounds + 1;m++)              {                  if (matchLevel[m] > matchLevel[tempIndex])                  {                      tempMax = matchLevel[m];                      tempIndex = m;                  }              }              dst = (unsigned char *)NCCImage->imageData + i*NCCImage->widthStep + j;              *dst = tempIndex*8;              dst = (unsigned char *)MatchLevelImage->imageData + i*MatchLevelImage->widthStep + j;              *dst = (unsigned char)(tempMax*255);          }      }      cvShowImage("Census",NCCImage);      cvShowImage("MatchLevel",MatchLevelImage);      cvSaveImage("depth.jpg",NCCImage);      cvSaveImage("matchLevel.jpg",MatchLevelImage);      cout<<endl<<"Over"<<endl;      cvWaitKey(0);      cvDestroyAllWindows();      cvReleaseImage(&leftImage);      cvReleaseImage(&rightImage);      return 0;  }  
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DP算法：

#include <cstdio>   #include <cstring>   #include <iostream>   #include<cv.h>   #include<highgui.h>   #include <cmath>   using namespace std;  const int Width =  1024;  const int Height = 1024;   int Ddynamic[Width][Width];  int  main()  {        /*Half of the window size for the census transform*/      int hWin = 11;      int compareLength = (2*hWin+1)*(2*hWin+1);      cout<<"hWin: "<<hWin<<";  "<<"compare length:  "<<compareLength<<endl;        cout<<"belief propagation test"<<endl;      IplImage * leftImage = cvLoadImage("l2.jpg",0);      IplImage * rightImage = cvLoadImage("r2.jpg",0);     // IplImage * leftImage = cvLoadImage("left.bmp",0);                                 // IplImage * rightImage = cvLoadImage("right.bmp",0);       int imageWidth = leftImage->width;      int imageHeight =leftImage->height;      IplImage * DPImage = cvCreateImage(cvGetSize(leftImage),leftImage->depth,1);      //IplImage * MatchLevelImage = cvCreateImage(cvGetSize(leftImage),leftImage->depth,1);       unsigned char * pPixel = NULL;      unsigned char  pixel;      for (int i = 0; i< imageHeight;i++)      {          for (int j =0; j < imageWidth;j++ )          {              pPixel = (unsigned char *)DPImage->imageData + i*DPImage->widthStep + j;              *pPixel = 0;          }      }      int minDBounds = 0;      int maxDBounds = 31;      cvNamedWindow("Left",1);      cvNamedWindow("Right",1);      cvNamedWindow("Depth",1);      cvNamedWindow("MatchLevel",1);      cvShowImage("Left",leftImage);      cvShowImage("Right",rightImage);      int minD = 0;      int maxD = 31;      //假设图像是经过矫正的，那么每次都只是需要搜搜同一行的内容       int max12Diff = 10;      for (int i = 0;i < imageWidth;i++)      {          Ddynamic[0][i] = 0;          Ddynamic[i][0] = 0;      }      unsigned char * pLeftPixel  = NULL;      unsigned char * pRightPixel = NULL;      unsigned char leftPixel = 0;      unsigned char rightPixel =0;      int m,n,l;      for (int i = 0 ; i < imageHeight;i++)      {          for (int j = 0; j<imageWidth;j++)          {              for (int k = j + minD; k <= j + maxD;k++)              {                  if (k <0 || k >= imageWidth)                  {                  }else {                      pLeftPixel = (unsigned char*)leftImage->imageData + i*leftImage->widthStep + k;                      pRightPixel= (unsigned char*)rightImage->imageData+i*rightImage->widthStep + j;                      leftPixel  = *pLeftPixel;                      rightPixel = *pRightPixel;                      if (abs(leftPixel - rightPixel) <= max12Diff)                      {                          Ddynamic[j + 1][k + 1] = Ddynamic[j][k] +1;                       }else if (Ddynamic[j][k+1] > Ddynamic[j+1][k])                      {                          Ddynamic[j + 1][k + 1] = Ddynamic[j][k+1];                      }else{                          Ddynamic[j+1][k+1] = Ddynamic[j+1][k];                      }                      //cout<<Ddynamic[j +1][k+1]<<"  ";                   }              }               //cout<<"\n";           }          //逆向搜索，找出最佳路径            m = imageWidth;           n = imageWidth;           l = Ddynamic[imageWidth][imageWidth];          while( l>0 )          {              if (Ddynamic[m][n] == Ddynamic[m-1][n])                    m--;              else if (Ddynamic[m][n] == Ddynamic[m][n-1])                    n--;              else              {                   //s[--l]=a[i-1];                   pPixel = (unsigned char *)DPImage->imageData + i*DPImage->widthStep + m;                  *pPixel = (n-m)*8;                  l--;                  m--;                   n--;              }          }         //cvWaitKey(0);       }      cvShowImage("Depth",DPImage);      cvSaveImage("depth.jpg",DPImage);      cvWaitKey(0);      return 0;  }  
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DP_5算法：

//引入概率公式   //   #include <cstdio>   #include <cstring>   #include <iostream>   #include<cv.h>   #include<highgui.h>   #include <cmath>   using namespace std;  const int Width =  1024;  const int Height = 1024;   int Ddynamic[Width][Width];   //使用钟形曲线作为匹配概率，差值越小则匹配的概率越大，最终的要求是使匹配的概率最大，概率曲线使用matlab生成    int Probability[256] = {      255, 255, 254, 252, 250, 247, 244, 240, 235, 230, 225, 219, 213, 206, 200, 192, 185, 178, 170, 162,       155, 147, 139, 132, 124, 117, 110, 103, 96, 89, 83, 77, 71, 65, 60, 55, 50, 46, 42, 38, 35, 31, 28,       25, 23, 20, 18, 16, 14, 13, 11, 10, 9, 8, 7, 6, 5, 4, 4, 3, 3, 2, 2, 2, 2, 1, 1, 1, 1, 1, 1, 0, 0,       0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0,       0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0,       0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0,       0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0,       0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0,       0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0   };  int  main()  {        IplImage * leftImage = cvLoadImage("l2.jpg",0);      IplImage * rightImage = cvLoadImage("r2.jpg",0);      //IplImage * leftImage = cvLoadImage("left.bmp",0);                                  //IplImage * rightImage = cvLoadImage("right.bmp",0);       int imageWidth = leftImage->width;      int imageHeight =leftImage->height;      IplImage * DPImage = cvCreateImage(cvGetSize(leftImage),leftImage->depth,1);      IplImage * effectiveImage = cvCreateImage(cvGetSize(leftImage),leftImage->depth,1);      IplImage * FilterImage = cvCreateImage(cvGetSize(leftImage),leftImage->depth,1);      unsigned char * pPixel = NULL;      unsigned char  pixel;      unsigned char * pPixel2 = NULL;      unsigned char  pixel2;      for (int i = 0; i< imageHeight;i++)      {          for (int j =0; j < imageWidth;j++ )          {              pPixel = (unsigned char *)DPImage->imageData + i*DPImage->widthStep + j;              *pPixel = 0;              pPixel = (unsigned char *)effectiveImage->imageData + i*effectiveImage->widthStep + j;              *pPixel = 0;          }      }      cvNamedWindow("Left",1);      cvNamedWindow("Right",1);      cvNamedWindow("Depth",1);      cvNamedWindow("effectiveImage",1);      cvShowImage("Left",leftImage);      cvShowImage("Right",rightImage);      int minD = 0;      int maxD = 31;      //假设图像是经过矫正的，那么每次都只是需要搜搜同一行的内容       int max12Diff = 5;      for (int i = 0;i < imageWidth;i++)      {          Ddynamic[0][i] = 0;          Ddynamic[i][0] = 0;      }      unsigned char * pLeftPixel  = NULL;      unsigned char * pRightPixel = NULL;      unsigned char leftPixel = 0;      unsigned char rightPixel =0;      int m,n,l;      int t1 = clock();      for (int i = 0 ; i < imageHeight;i++)      {          for (int j = 0; j<imageWidth;j++)          {              for (int k = j + minD; k <= j + maxD;k++)              {                  if (k <0 || k >= imageWidth)                  {                  }else {                      pLeftPixel = (unsigned char*)leftImage->imageData + i*leftImage->widthStep + k;                      pRightPixel= (unsigned char*)rightImage->imageData+i*rightImage->widthStep + j;                      leftPixel  = *pLeftPixel;                      rightPixel = *pRightPixel;                      //之前概率最大的点加上当前的概率                       Ddynamic[j + 1][k + 1] = max(Ddynamic[j][k],max(Ddynamic[j][k+1],Ddynamic[j+1][k]))                                               + Probability[abs(leftPixel - rightPixel)];                      /* if (abs(leftPixel - rightPixel) <= max12Diff)                     {                     Ddynamic[j + 1][k + 1] = Ddynamic[j][k] +1;                      }else if (Ddynamic[j][k+1] > Ddynamic[j+1][k])                     {                     Ddynamic[j + 1][k + 1] = Ddynamic[j][k+1];                     }else{                     Ddynamic[j+1][k+1] = Ddynamic[j+1][k];                     }*/                      //cout<<Ddynamic[j +1][k+1]<<"  ";                   }              }               //cout<<"\n";           }          //逆向搜索，找出最佳路径            m = imageWidth;           n = imageWidth;           l = Ddynamic[imageWidth][imageWidth];          while( m >= 1 && n >= 1)          {              pPixel = (unsigned char *)DPImage->imageData + i*DPImage->widthStep + m;              *pPixel = (n-m)*8;              //标记有效匹配点               pPixel = (unsigned char *)effectiveImage->imageData + i*effectiveImage->widthStep + m;              *pPixel = 255;              if (Ddynamic[m-1][n] >= Ddynamic[m][n -1] && Ddynamic[m-1][n] >= Ddynamic[m-1][n -1])                    m--;              else if (Ddynamic[m][n-1] >= Ddynamic[m-1][n] && Ddynamic[m][n -1] >= Ddynamic[m-1][n -1])                    n--;              else              {                   //s[--l]=a[i-1];                         // l -= Ddynamic[m][n];                   m--;                   n--;              }          }         //cvWaitKey(0);       }      //refine the depth image  7*7中值滤波       //统计未能匹配点的个数       int count = 0;      for (int i = 0 ;i< imageHeight;i++)      {          for (int j= 0; j< imageWidth;j++)          {              pPixel = (unsigned char *)effectiveImage->imageData + i*effectiveImage->widthStep + j;              pixel = *pPixel;              if (pixel == 0)              {                  count++;              }          }      }      int t2 = clock();      cout<<"dt: "<<t2-t1<<endl;      cout<<"Count:  "<<count<<"  "<<(double)count/(imageWidth*imageHeight)<<endl;      cvShowImage("Depth",DPImage);      cvShowImage("effectiveImage",effectiveImage);     // cvWaitKey(0);       FilterImage = cvCloneImage(DPImage);      //7*7中值滤波       int halfMedianWindowSize = 3;      int medianWindowSize = 2*halfMedianWindowSize + 1;      int medianArray[100] = {0};      count = 0;      int temp = 0;      int medianVal = 0;      for (int i = halfMedianWindowSize + 1 ;i< imageHeight - halfMedianWindowSize;i++)      {          for (int j = halfMedianWindowSize; j< imageWidth - halfMedianWindowSize;j++)          {              pPixel = (unsigned char *)effectiveImage->imageData + i*effectiveImage->widthStep + j;              pixel = *pPixel;              if (pixel == 0)              {                  count = 0;                  for (int m = i - halfMedianWindowSize ; m <= i + halfMedianWindowSize ;m++)                  {                      for (int n = j - halfMedianWindowSize; n <= j + halfMedianWindowSize ;n++)                      {                          pPixel2 = (unsigned char *)DPImage->imageData + m*DPImage->widthStep + n;                          pixel2 = *pPixel2;                          if (pixel2 != 0)                          {                               medianArray[count] = pixel2;                               count++;                          }                      }                      //排序                       for (int k = 0; k< count;k++)                      {                          for (int l = k + 1; l< count;l++)                          {                              if (medianArray[l] < medianArray[l-1] )                              {                                  temp = medianArray[l];                                  medianArray[l] = medianArray[l-1];                                  medianArray[l-1] = temp;                              }                          }                      }                      medianVal = medianArray[count/2];                      pPixel = (unsigned char *)FilterImage->imageData + i*DPImage->widthStep + j;                      *pPixel = medianVal;                  }              }          }      }      cvShowImage("Depth",DPImage);      cvShowImage("effectiveImage",effectiveImage);      cvShowImage("Filter",FilterImage);      cvSaveImage("depth.jpg",DPImage);      cvSaveImage("effective.jpg",effectiveImage);      cvWaitKey(0);      return 0;  }  
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