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Hi, I am using SVD for my algorithm and the decomposition is done by this instruction: const int N= 16; Mat x= (Mat_<double>(N, N)<< 23, 24, 24, 23, 22.5, 21.5, 20, 20, 19, 20, 22, 23, 23, 23.5, 24, 25.5, 23.5, 24, 23, 21, 21, 22, 21, 20, 18.5, 18, 19, 20, 20.5, 23, 24, 24, 24, 24, 22, 21, 21.5, 21.5, 21, 20, 19.5, 20, 21, 21, 22, 23, 24, 24, 24.5, 24, 23, 23, 23, 21, 20, 20, 20, 22, 22, 22, 23, 23, 24, 24, 24, 24, 24, 24, 24, 22, 20, 20, 20, 21, 21, 21, 21, 22, 24, 24, 24, 24.5, 25, 24.5, 24, 22, 20, 21, 21, 21, 22, 22, 22, 23, 24, 24, 24, 24.5, 25, 24.5, 24, 22, 20, 22, 23, 23, 24, 24, 23, 22, 22.5, 23, 24.5, 24.5, 24, 24, 23, 22, 22, 23, 24.5, 24.5, 23, 21.5, 21, 21, 22.5, 22.5, 23.5, 24.5, 25.5, 25, 23.5, 24.5, 26, 25.5, 24, 25, 22.5, 20.5, 20.5, 21, 21, 20.5, 24.5, 25.5, 26, 25.5, 24.5, 25, 25.5, 25, 24, 24, 22, 20.5, 20.5, 19.5, 18.5, 19.5, 25.5, 25.5, 26, 26, 25, 25, 25, 25, 23.5, 24, 22, 20, 20, 19.5, 18.5, 21, 24, 24, 24, 24, 24, 24.5, 23, 22.5, 24, 24.5, 23, 20.5, 20, 20, 20.5, 22.5, 24, 24, 24, 24, 24, 24, 23, 22.5, 24, 23.5, 23, 21.5, 20, 19.5, 22, 24, 22.5, 23, 22.5, 22, 23, 23, 22, 21.5, 23, 22, 22, 22, 20, 20.5, 23, 24, 22.5, 21.5, 21.5, 22, 23, 24, 22.5, 20, 21, 20.5, 20.5, 22, 22, 23, 23.5, 23.5, 22.5, 21, 21, 21, 21, 23, 21.5, 20, 20, 20.5, 20.5, 22, 24, 24, 23.5, 23.5); Mat Sigma= Mat::zeros(N, N, CV_64FC1); Mat S, U, VT, x_hat, err;
int minLoc[2], maxLoc[2]; double minVal, maxVal; SVDecomp(x, S, U, VT, cv::SVD::FULL_UV); /Please note that S is a column vector and S should be a square diagonal matrix, Assigning the components of the S to the diagonal components of Sigma/ x_hat= U * Sigma* VT; cout<< "U * Sigma* VT= "<< endl<< x_hat<< endl; absdiff(x, x_hat, err); And the error is really huge!!! (Terminal output) Reconstruction err: MIN= 0.00135955, MAX= 2.99473, sum= [176.076, 0, 0, 0] Which is shit! The whole process is done very straight forward with matlab. What's wrong with opencv SVD? Why does the operation loon irreversible?!!!! Your advices are highly appreciated. minMaxIdx(err, &minVal, &maxVal, minLoc, maxLoc); cout<< "Reconstruction err: MIN= "<< minVal<< ", MAX= "<< maxVal<< ", sum= "<< sum(err)<< endl; for (i1= 0; i1< N; i1++) Sigma.at<double>(i1, i1)= S.at<double>(i1, i1);

Hi, I am using SVD for my algorithm and the decomposition is done by this instruction:

const int N= 16;
 Mat x= (Mat_<double>(N, N)<< 23, 24, 24, 23, 22.5, 21.5, 20, 20, 19, 20, 22, 23,    23, 23.5, 24, 25.5,
         23.5, 24, 23, 21, 21, 22, 21, 20, 18.5, 18, 19, 20, 20.5, 23, 24, 24,
         24, 24, 22, 21, 21.5, 21.5, 21, 20, 19.5, 20, 21, 21, 22, 23, 24, 24,
         24.5, 24, 23, 23, 23, 21, 20, 20, 20, 22, 22, 22, 23, 23, 24, 24,
         24, 24, 24, 24, 24, 22, 20, 20, 20, 21, 21, 21, 21, 22, 24, 24,
         24, 24.5, 25, 24.5, 24, 22, 20, 21, 21, 21, 22, 22, 22, 23, 24, 24,
         24, 24.5, 25, 24.5, 24, 22, 20, 22, 23, 23, 24, 24, 23, 22, 22.5, 23,
         24.5, 24.5, 24, 24, 23, 22, 22, 23, 24.5, 24.5, 23, 21.5, 21, 21, 22.5, 22.5,
         23.5, 24.5, 25.5, 25, 23.5, 24.5, 26, 25.5, 24, 25, 22.5, 20.5, 20.5, 21, 21, 20.5,
         24.5, 25.5, 26, 25.5, 24.5, 25, 25.5, 25, 24, 24, 22, 20.5, 20.5, 19.5, 18.5, 19.5,
         25.5, 25.5, 26, 26, 25, 25, 25, 25, 23.5, 24, 22, 20, 20, 19.5, 18.5, 21,
         24, 24, 24, 24, 24, 24.5,   23, 22.5, 24, 24.5, 23, 20.5, 20, 20, 20.5, 22.5,
         24, 24, 24, 24, 24, 24, 23, 22.5, 24, 23.5, 23, 21.5, 20, 19.5, 22, 24,
         22.5, 23, 22.5, 22, 23, 23, 22, 21.5, 23, 22, 22, 22, 20, 20.5, 23, 24,
         22.5, 21.5, 21.5, 22, 23, 24, 22.5, 20, 21, 20.5, 20.5, 22, 22, 23, 23.5, 23.5,
         22.5, 21, 21, 21, 21, 23, 21.5, 20, 20, 20.5, 20.5, 22, 24, 24, 23.5, 23.5);
 Mat Sigma= Mat::zeros(N, N, CV_64FC1);
 Mat S, U, VT, x_hat, err; 
  int minLoc[2], maxLoc[2];
 double minVal, maxVal;
 SVDecomp(x, S, U, VT, cv::SVD::FULL_UV);
    /Please /*Please note that S is a column vector and S should be a square diagonal matrix, Assigning the components of the S    to the diagonal components of Sigma/
    Sigma*/
x_hat= U * Sigma* VT;
 cout<< "U * Sigma* VT= "<< endl<< x_hat<< endl;
 absdiff(x, x_hat, err); 
err);

And the error is really huge!!! (Terminal output)

Reconstruction err: MIN= 0.00135955, MAX= 2.99473, sum= [176.076, 0, 0, 0]

Which is shit! The whole process is done very straight forward with matlab. What's wrong with opencv SVD? Why does the operation loon irreversible?!!!! Your advices are highly appreciated. appreciated.

minMaxIdx(err, &minVal, &maxVal, minLoc, maxLoc);
 cout<< "Reconstruction err: MIN= "<< minVal<< ", MAX= "<< maxVal<< ", sum= "<< sum(err)<< endl;
 for (i1= 0; i1< N; i1++)
     Sigma.at<double>(i1, i1)= S.at<double>(i1, i1); 
i1);