public Bilateral(double sigmaD, double sigmaR)
{
// compute the necessary kernel radius from the maximum of both sigma values
double sigmaMax = Math.Max(sigmaD, sigmaR);
int kernelRadius = (int)Math.Ceiling(2 * sigmaMax);
this.SigmaD = sigmaD;
this.SigmaR = sigmaR;
this.TwoSigmaRSquared = 2 * this.SigmaR * this.SigmaR;
this.Size = kernelRadius * 2 + 1;
int center = (this.Size - 1) / 2;
Gaussian gauss = new Gaussian(sigmaD);
this.KernelD = gauss.Kernel2D(this.Size);
for (int x = -center; x < -center + this.Size; x++)
{
for (int y = -center; y < -center + this.Size; y++)
{
this.KernelD[x + center, y + center] = gauss.Function2D(x, y);
}
}
// precomute all possible similarity values for performance resaons
this.GaussSimilarity = new double[256];
for (int i = 0; i < 256; i++)
{
this.GaussSimilarity[i] = Math.Exp(-((i) / this.TwoSigmaRSquared));
}
}