立体匹配之NCC算法
FROM:http://blog.csdn.net/tulun/article/details/6388759
NCC算法(Normal Cross Correlation),具体原理见相关图像处理书籍。
该程序是opencv中文论坛的牛人贡献的,感谢他的工作。
(程序所需图片可以在网上找如http://vision.middlebury.edu/stereo/data/scenes2003/)
#include <iostream>
#include <stdio.h>
#include <stdlib.h>
#include <cv.h>
#include <cxcore.h>
#include <highgui.h>
#include <math.h>
#include <ctime>
using namespace std;
template<class T> class Image
{
private:
IplImage* imgp;
public:
Image(IplImage* img=0){imgp=img;}
~Image(){imgp=0;}
void operator=(IplImage* img){imgp=img;}
inline T* operator[](const int rowIndx)
{
return((T*)(imgp->imageData+rowIndx*imgp->widthStep));
}
};
typedef struct
{
unsigned char b,g,r;
}RgbPixel;
typedef struct
{
float b,g,r;
}RgbPixelFloat;
typedef Image<RgbPixel> RgbImage;
typedef Image<RgbPixelFloat> RgbImageFloat;
typedef Image<unsigned char> BwImage;
typedef Image<float> BwImageFloat;
void displayImageProperty(IplImage* image)
{
cout<<"-------Image Properties--------"<<endl;
cout<<"Image width="<<image->width<<endl;
cout<<"Image height="<<image->height<<endl;
cout<<"Image depth="<<image->depth<<endl;
cout<<"Image nSize="<<image->nSize<<endl;
cout<<"Image nChannels="<<image->nChannels<<endl;
char* origin;
char* dataOrder;
if (image->origin==0)
{
origin="Top-left";
}
else
{
origin="Below-left";//image->origin=1
}
cout<<"Image origin="<<origin<<endl;
if (image->dataOrder==0)
{
dataOrder="Order_Pixel(Interleaved)";
}
else
{
dataOrder="Order_Plane";//image->dataOrder=1
}
cout<<"Image dataOrder="<<dataOrder<<endl;
cout<<"Image widthStep="<<image->widthStep<<" Bytes"<<endl;
}
// display an image in a new window with title to be given.
void displayImageNewWindow(char* title,CvArr* img)
{
cvNamedWindow(title, CV_WINDOW_AUTOSIZE );
cvShowImage(title,img);
}
int getMaxMin(double value[],int valueSize, int maxmin)
{
int pos=0;
int i=0;
double max1=-1;//?-999999;
double min1=999999;
if (maxmin==1)
{
//find max
for (i=0;i<valueSize;i++)
{
//find the index with the max ncc;
if (value[i]>max1)
{
pos=i;
max1=value[i];
}
}
}
if (maxmin==0)
{
//find min
for (i=0;i<valueSize;i++)
{
//find the index with the max ncc;
if (value[i]<min1)
{
pos=i;
min1=value[i];
}
}
}
return pos;
}
IplImage* generateDisparityImage(IplImage* greyLeftImg32,IplImage* greyRightImg32,int windowSize,int DSR)
{
int offset=floor((double)windowSize/2);
int height=greyLeftImg32->height;
int width=greyLeftImg32->width;
double* localNCC=new double[DSR];
int x=0, y=0,d=0,m=0;
int N=windowSize;
IplImage* leftWinImg=cvCreateImage(cvSize(N,N),32,1);//mySubImage(greyLeftImg32,cvRect(0,0,N,N));
IplImage* rightWinImg=cvCreateImage(cvSize(N,N),32,1);;//mySubImage(greyRightImg32,cvRect(0,0,N,N));
IplImage* disparity=cvCreateImage(cvSize(width,height),8,1);//or IPL_DEPTH_8U
BwImage imgA(disparity);
for (y=0;y<height;y++)
{
for (x=0;x<width;x++)
{
imgA[y][x]=0;
}
}
CvScalar s1;
CvScalar s2;
for (y=0;y<height-N;y++)
{
//height-N
for (x=0;x<width-N;x++)
{
//width-N
//getWindow(i,j,leftim,wl,N);
cvSetImageROI(greyLeftImg32, cvRect(x,y,N,N));
s1=cvAvg(greyLeftImg32,NULL);
cvSubS(greyLeftImg32,s1,leftWinImg,NULL);//zero-means
cvNormalize(leftWinImg,leftWinImg,1,0,CV_L2,NULL);//0变成1
d=0;
//initialise localNCC
for (m=0;m<DSR;m++)
{
localNCC[m]=0;
}
do{
if (x-d>=0)
{
cvSetImageROI(greyRightImg32, cvRect(x-d,y,N,N));
s2=cvAvg(greyRightImg32,NULL);
cvSubS(greyRightImg32,s2,rightWinImg,NULL);//zero-means
cvNormalize(rightWinImg,rightWinImg,1,0,CV_L2,NULL);//0变成1
}
else
{
break;
}
localNCC[d]=cvDotProduct(leftWinImg,rightWinImg);
cvResetImageROI(greyRightImg32);
d++;
}while(d<=DSR);
//to find the best d and store
imgA[y+offset][x+offset]=getMaxMin(localNCC,DSR,1)*16;
cvResetImageROI(greyLeftImg32);
}//x
if (y%10==0)
cout<<"row="<<y<<" of "<<height<<endl;
}//y
cvReleaseImage(&leftWinImg);
cvReleaseImage(&rightWinImg);
return disparity;
}
int main (int argc, char * const argv[])
{
// insert code here...
cout << "Stereo Normalized Cross Correlation"<<endl;
//**********image input*********************//
char* filename1="im0.ppm";//im2_cone.png
IplImage* greyLeftImg= cvLoadImage(filename1,0);
char* filename2="im1.ppm";
IplImage* greyRightImg= cvLoadImage(filename2,0);
if (greyLeftImg==NULL)
{
cout << "No valid image input."<<endl;
//char c=getchar();
return 1;
}
else
{
displayImageProperty(greyLeftImg);
}
if (greyRightImg==NULL)
{
cout << "No valid image input."<<endl;
//char c=getchar();
return 1;
}
int width=greyLeftImg->width;
int height=greyLeftImg->height;
/****************8U to 32F**********************/
IplImage* greyLeftImg32=cvCreateImage(cvSize(width,height),32,1);//IPL_DEPTH_32F
IplImage* greyRightImg32=cvCreateImage(cvSize(width,height),32,1);
cvConvertScale(greyLeftImg, greyLeftImg32, 1/255.);
cvConvertScale(greyRightImg, greyRightImg32, 1/255.);//1/255. equals to 1/255.0
//-------------Computing stereo matching----------------
time_t tstart, tend;
tstart = time(0);
int windowSize=11,DSR=20;//Disparity Search Range
IplImage* disparity32=generateDisparityImage(greyLeftImg32,greyRightImg32,windowSize,DSR);
tend = time(0);
cout << "It took "<< difftime(tend, tstart) <<" second(s)."<< endl;
displayImageNewWindow("Dispairty Image",disparity32);
displayImageNewWindow("Left Image",greyLeftImg32);
displayImageNewWindow("Right Image",greyRightImg32);
//cvSaveImage("D:/OpenCV_stuff/SampleImages/disparity.jpg",disparity32);
//********destroy window************/
cvWaitKey(0);
cvReleaseImage(&greyLeftImg32);
cvReleaseImage(&greyRightImg32);
cvReleaseImage(&greyLeftImg);
cvReleaseImage(&greyRightImg);
cvReleaseImage(&disparity32);
cvDestroyWindow("Left Image");
cvDestroyWindow("Right Image");
cvDestroyWindow("Dispairty Image");
return 0;
}
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