I have this code (revisited version of this):
void HessianDetector::detectOctaveKeypoints(const Mat &firstLevel, ...)
{
vector<Mat> blurs (par.numberOfScales+3, Mat());
blurs[1] = firstLevel;
for (int i = 1; i < par.numberOfScales+2; i++){
float sigma = par.sigmas[i]* sqrt(sigmaStep * sigmaStep - 1.0f);
blurs[i+1] = gaussianBlur(blurs[i], sigma);
}
...
Where:
Mat gaussianBlur(const Mat input, const float sigma)
{
Mat ret(input.rows, input.cols, input.type());
int size = (int)(2.0 * 3.0 * sigma + 1.0); if (size % 2 == 0) size++;
GaussianBlur(input, ret, Size(size, size), sigma, sigma, BORDER_REPLICATE);
return ret;
}
So, as you can see, each blurs[i+1] depends on blurs[i], so it cannot be parallelized. My question is: is there an equivalent way to obtain the same result but using firstLevel instead of blurs[i]? So it should so look something like:
for (int i = 1; i < par.numberOfScales+2; i++){
float sigma = //something;
blurs[i+1] = gaussianBlur(firstLevel, sigma);
}
Is it possible?
This answer let me think that it's possible, but I can't understand how I can implement this:
Convolve filters If you apply multiple filters on the same image consecutively, like a gaussian blur, then a Gabor filter, you can combine them together. Make all filters the same size and convolve them. Then apply the result on the image. Math says the effect will be identical with the previous combination