// 0 sigma, 1 gamma, 2 theta, 3 lambda, 4 psi
public static ConvolutionKernel CalculateGaborKernel(List <double> param,
Func <int, int, List <double>, float> function) //todo check formula
{
int sm = (int)param[0];
int half = 3 * sm;
int size = 6 * sm + 1;
ConvolutionKernel kernel = new ConvolutionKernel();
kernel.Kernel = new float[size * size];
float sum = 0;
for (int j = 0; j < size; j++)
{
for (int i = 0; i < size; i++)
{
float val = function(i - half, j - half, param);
kernel.Kernel[j * size + i] = val;
sum += val;
}
}
kernel.Sum = sum;
return(kernel);
}
public static List <ConvolutionKernel> CalculateKernelXY(double sigma,
Func <int, int, double, float> function) //todo check formula
{
int sm = (int)sigma;
int half = 3 * sm;
int size = 6 * sm + 1;
ConvolutionKernel kernelX = new ConvolutionKernel();
kernelX.Kernel = new float[size * size];
kernelX.Sum = 0;
ConvolutionKernel kernelY = new ConvolutionKernel();
kernelY.Kernel = new float[size * size];
kernelY.Sum = 0;
for (int j = 0; j < size; j++)
{
for (int i = 0; i < size; i++)
{
var valX = function(i - half, j - half, sigma);
var valY = function(j - half, i - half, sigma);
kernelX.Kernel[j * size + i] = valX;
kernelY.Kernel[j * size + i] = valY;
kernelX.Sum += Math.Abs(valX);
kernelY.Sum += Math.Abs(valY);
}
}
return(new List <ConvolutionKernel>()
{
kernelX, kernelY
});
}
public static ConvolutionKernel CalculateKernel(double sigma,
Func <int, int, double, float> function) //todo check formula
{
int sm = (int)sigma;
int half = 3 * sm;
int size = 6 * sm + 1;
ConvolutionKernel kernel = new ConvolutionKernel();
kernel.Kernel = new float[size * size];
float sum = 0;
for (int j = 0; j < size; j++)
{
for (int i = 0; i < size; i++)
{
float val = function(i - half, j - half, sigma);
kernel.Kernel[j * size + i] = val;
sum += val;
}
}
kernel.Sum = sum;
return(kernel);
}
public static GrayscaleFloatImage Gabor(ColorFloatImage image, double sigma,
double gamma, double theta, double lambda,
double psi)
{
List <double> param = new List <double>();
param.Add(sigma);
param.Add(gamma);
param.Add(DegreeToRadian(theta));
param.Add(lambda);
param.Add(psi);
ConvolutionKernel kernel = CalculateGaborKernel(param, GaborPoint);
return(GradientGrayscale(image, kernel.Kernel, 1));
}
public static List <GrayscaleFloatImage> MagnitudeAndDirections(ColorFloatImage image,
ConvolutionKernel xKernel, ConvolutionKernel yKernel)
{
var xWindow = xKernel.Kernel;
var yWindow = yKernel.Kernel;
GrayscaleFloatImage magn = new GrayscaleFloatImage(image.Width, image.Height);
GrayscaleFloatImage angles = new GrayscaleFloatImage(image.Width, image.Height);
int windowSide = (int)Math.Pow(xWindow.Length, 0.5);
int halfWindowSide = (windowSide - 1) / 2;
for (int y = 0; y < image.Height; y++)
{
for (int x = 0; x < image.Width; x++)
{
List <int> i = NeighbourIndexes(x, image.Width - 1, halfWindowSide, FillMode.Reflection);
List <int> j = NeighbourIndexes(y, image.Height - 1, halfWindowSide, FillMode.Reflection);
List <float> pix = new List <float>();
for (int k = 0; k < windowSide; k++)
{
for (int n = 0; n < windowSide; n++)
{
pix.Add(RGB2GrayPix(image[i[n], j[k]]));
}
}
float xPix = ConvolveGray(xWindow, pix, xKernel.Sum);
float yPix = ConvolveGray(yWindow, pix, yKernel.Sum);
magn[x, y] = (float)Math.Sqrt(Math.Pow(xPix, 2) + Math.Pow(yPix, 2));
angles[x, y] = FitAngleInBin(Math.Abs(Math.Atan2(yPix, xPix)));
}
}
return(new List <GrayscaleFloatImage>()
{
magn, angles
});
}
public static GrayscaleFloatImage GaussMagnitude(ColorFloatImage image, float sigma)
{
ConvolutionKernel kernel = CalculateKernel(sigma, LoGPoint);
return(GradientGrayscale(image, kernel.Kernel, 1));
}
public static ColorFloatImage Gauss(ColorFloatImage image, float sigma)
{
ConvolutionKernel kernel = CalculateKernel(sigma, GaussPoint);
return(Gradient(image, kernel.Kernel, kernel.Sum));
}