Calculate Covariance

asked 2016-03-29 11:41:14 -0600

willoughby gravatar image

updated 2016-03-29 11:42:07 -0600

I have a matrix (an image). And I want to calculate the covariance of the colors. However, there are sections of the matrix that are blank (-1,-1,-1) that I want to ignore in the covariance calculation. Currently, I am doing this process manually like so :

  1. iterate over every pixel: if not equal to (-1,-1,-1) subtract mean color (calculated during matrix generation), if equal to (-1,-1,-1) set to (0,0,0)

  2. Split Matrix into 3 color matrices

  3. Reshape each color matrices into column matrix

  4. Recombine column color matrices

  5. Multiply by transpose and divide by count - 1 (count does not include (-1,-1,-1) pixels)

I would like to add GPU (CUDA) support and use calcCovarMatrix() However I don't know if it is possible to get this function to perform this operation. Any help would be nice.

PS. Here is my Code

updateCovariance(cv::Mat matrix, cv::Mat covariance Vec3f averageColor, int count){
cv::Mat meanDifference(matrix.rows,matrix.cols,matrix.type());

std::vector<cv::Mat> colors(3);
std::vector<cv::Mat> columnColor(3, cv::Mat(matrix.rows*matrix.cols,1,matrix.type()));

cv::Mat colorMat(matrix.rows*matrix.cols,3,matrix.type());
cv::Mat colorMatTrans(3,matrix.rows*matrix.cols,matrix.type());

for(int y = 0; y < meanDifference.rows; ++y)
    for (int x=0; x<meanDifference.cols; ++x)
        if (<cv::Vec3f>(y,x) != cv::Vec3f(-1,-1,-1))
  <cv::Vec3f>(y,x) =<cv::Vec3f>(y,x)-averageColor;
  <cv::Vec3f>(y,x) = cv::Vec3f(0,0,0);

//Reshape Color Matrices into column arrays
for(int i=0;i < colors.size();++i)
    columnColor[i] = colors[i].reshape(1,1);

//Recombine color matrices and transpose


covariance = (colorMat * colorMatTrans)/(count-1);
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