相机校正（实现）

关于相机校正,opencv自带了程序，隐藏在calibration.cpp文件里，期初没有在意，后来才恍然大悟。我先贴出这段程序;

#include <iostream> 
#include <cmath> 
#include "opencv2/opencv.hpp" 


using namespace cv; 
using namespace std; 
#define threshold_diff 20 


int main(int, char**) 
{ 
VideoCapture cap; 
cap.open(1); 


if( !cap.isOpened() ) 
return -1; 


Mat prevgray, gray, frame; 
Mat intrinsic = Mat(3, 3, CV_32FC1); 
intrinsic.at<float>(0, 0) = 321.2398; 
intrinsic.at<float>(0, 1) = 0; 
intrinsic.at<float>(0, 2) = 335.4872; 
intrinsic.at<float>(1, 0) = 0; 
intrinsic.at<float>(1, 1) = 391.6564; 
intrinsic.at<float>(1, 2) = 236.4062; 
intrinsic.at<float>(2, 0) = 0; 
intrinsic.at<float>(2, 1) = 0; 
intrinsic.at<float>(2, 2) = 1; 

Mat distcoeffs = Mat(5,1,CV_32FC1); 
distcoeffs.at<float>(0,0) = -0.3257; 
distcoeffs.at<float>(1,0) = -1.5232; 
distcoeffs.at<float>(2,0) = -0.0007; 
distcoeffs.at<float>(3,0) = -0.0020; 
distcoeffs.at<float>(4,0) = -0.0452; 


Mat map1,map2,rview; 
Size imageSize,newImageSize;  


Mat imgU; 
for(;;) 
{ 
double t = (double)cvGetTickCount(); 


cap >> frame; 
imageSize.width = frame.cols; 
imageSize.height = frame.rows; 
newImageSize.width = imageSize.width; 
newImageSize.height = imageSize.height; 


imshow("original", frame); 
//undistort(frame, imgU, intrinsic, distcoeffs); 
initUndistortRectifyMap(intrinsic, distcoeffs, Mat(), 
getOptimalNewCameraMatrix(intrinsic, distcoeffs, imageSize, 1, newImageSize, 0), 
newImageSize, CV_16SC2, map1, map2); 
remap(frame, rview, map1, map2, INTER_LINEAR); 
imshow("rview",rview); 
cvtColor(rview, gray, CV_BGR2GRAY); 
//imshow("undistort", imgU); 


Mat flowmap; 
Mat diff; 
if( prevgray.data ) 
{ 
subtract(gray,prevgray,diff); 
for(int i=0;i<diff.rows;i++) 
for(int j=0;j<diff.cols;j++) 
if(abs(diff.at<unsigned char>(i,j))>=threshold_diff)//这里模板参数一定要用unsigned char，否则就一直报错 
diff.at<unsigned char>(i,j)=255; 
else diff.at<unsigned char>(i,j)=0; 
imshow("diff",diff); //直接在判断内显示，imshow才不会出错 
} 
if(waitKey(10)>=0) 
break; 
std::swap(prevgray, gray); 
t = (double)cvGetTickCount() - t; 
cout << "cost time: " << t / ((double)cvGetTickFrequency()*1000) << endl; 
} 
return 0; 
} 

一般有两种方法，1种是采用remap进行校正，1种是采用undistort进行校正。在我采用undistort输出的校正图片比较可观，而采用remap却反而比原始图片更糟糕，如下图

期初觉得是没有标定好，然后又选择了一组图片，得到的效果还是一样的。
具体的原因还在调查中…