private void InitGaussianDerivative(double standardDeviation, int order, double norm)
{
Debug.Assert(order >= 0);
if (order == 0)
{
InitGaussian(standardDeviation, norm);
return;
}
Debug.Assert(standardDeviation > 0.0);
Gaussian gauss = new Gaussian(standardDeviation, order);
// First calculate the required kernel size
int radius = (int)(3.0 * standardDeviation + 0.5 * order + 0.5);
if (radius == 0)
{
radius = 1;
}
kernel.Clear();
kernel.Capacity = radius * 2 + 1;
// Fill the kernel and calculate the DC component
// introduced by truncation of the Gaussian
double dc = 0.0;
for (int x = -radius; x <= radius; ++x)
{
kernel.Add(gauss.Value(x));
dc += kernel[kernel.Count - 1];
}
dc /= 2.0 * radius + 1.0;
// Remove the DC component, but only if kernel correction
// is permitted by a non-zero value for the norm
if (norm != 0.0)
{
for (int i = 0; i < kernel.Count; ++i)
{
kernel[i] -= dc;
}
}
left = -radius;
right = radius;
if (norm != 0.0)
{
Normalize(norm, order);
}
else
{
this.norm = 1.0;
}
// The best border treatment for Gaussian derivatives in repeat
borderTreatment = BorderTreatmentMode.BorderTreatmentRepeat;
}
public void InitGaussian(double standardDeviation, double norm)
{
Debug.Assert(standardDeviation >= 0.0);
Gaussian gauss = new Gaussian(standardDeviation);
if (standardDeviation > 0.0)
{
int radius = (int)(3 * standardDeviation + 0.5);
if (radius == 0)
{
radius = 1;
}
kernel.Clear();
kernel.Capacity = radius * 2 + 1;
for (int x = -radius; x <= radius; ++x)
{
kernel.Add(gauss.Value(x));
}
left = -radius;
right = radius;
}
else
{
kernel.Clear();
kernel.Add(1.0);
left = 0;
right = 0;
}
if (norm != 0.0)
{
Normalize(norm);
}
else
{
this.norm = 1.0;
}
// Best border treatment for Gaussians is clip
borderTreatment = BorderTreatmentMode.BorderTreatmentClip;
}
