Fitting 2d gauss function in C++ too slow

Question

I'm trying to fit a 2d gauss function to an image (in cv::Mat format), and I'm using the NLopt library.

I put my object function like this:

for(i for each row)
    for(j for each col)
    {
        //compute the gauss function value
        double valuenow=x[0]*exp(-( x[3]*(j-x[1])*(j-x[1]) + 2*x[4]*(j-x[1])*(i-x[2]) + x[5]*(i-x[2])*(i-x[2]) ));
        //add square residual to result
        result+=(valuenow-fitdata.at<double>(i,j))*(valuenow-fitdata.at<double>(i,j));
    }
return result;

My matrix is about 1000*1000 size, I'm using LN_COBYLA algorithm. When I ran this, it turned out to be extremely slow. I think there must be something wrong with the way I specify my object function, because I used to do the same thing in Matlab with lsqnonlinear, which returned in a second.

Can someone help me please? Thanks in advance.

Answer 1

The at<>() function is slow. If speed is of essence, it's not a good idea to use it inside loops. Take a pointer outside the loop and then just use that pointer inside the loop.

A related question: OpenCV Mat array access, which way is the fastest for and why?