public static Complex[,] EsimateH2(double[,] img, double Sigma1, double Sigma2)
{
var z = GetSquaredDerectionField(img, Sigma1);
var kernel2 = KernelHelper.MakeComplexKernel((x, y) => Gaussian.Gaussian2D(x, y, Sigma2) * x, (x, y) => Gaussian.Gaussian2D(x, y, Sigma2) * (-y), KernelHelper.GetKernelSizeForGaussianSigma(Sigma2));
var I20 = ConvolutionHelper.ComplexConvolve(z, kernel2);
return(I20);
}
public static double[,] Reduce2(double[,] source, double factor)
{
var smoothed = ConvolutionHelper.Convolve(source,
KernelHelper.MakeKernel(
(x, y) => Gaussian.Gaussian2D(x, y, factor / 2d * 0.75d), KernelHelper.GetKernelSizeForGaussianSigma(factor / 2d * 0.75d)));
var result = new double[(int)(source.GetLength(0) / factor), (int)(source.GetLength(1) / factor)];
Resize(smoothed, result, factor, (x, y) => Gaussian.Gaussian2D(x, y, factor / 2d * 0.75d));
return(result);
}
private static double[,] FilterFrequencies(double[,] frequencyMatrix, int filterSize, double sigma, int w)
{
var result = new double[frequencyMatrix.GetLength(0), frequencyMatrix.GetLength(1)];
var lowPassFilter = new Filter(filterSize, sigma);
lowPassFilter.Normalize();
result = ConvolutionHelper.Convolve(frequencyMatrix, lowPassFilter.Matrix, w);
return(result);
}
public static Complex[,] GetSquaredDerectionField(double[,] img, double Sigma1)
{
var kernelX = KernelHelper.MakeKernel((x, y) => Gaussian.Gaussian2D(x, y, Sigma1) * x, KernelHelper.GetKernelSizeForGaussianSigma(Sigma1));
var resultX = ConvolutionHelper.Convolve(img, kernelX);
var kernelY = KernelHelper.MakeKernel((x, y) => Gaussian.Gaussian2D(x, y, Sigma1) * -y, KernelHelper.GetKernelSizeForGaussianSigma(Sigma1));
var resultY = ConvolutionHelper.Convolve(img, kernelY);
var preZ = KernelHelper.MakeComplexFromDouble(resultX, resultY);
var z = preZ.Select2D(x => x * x);
return(z);
}
public static Complex[,] EstimatePS(double[,] img, double Sigma1, double Sigma2)
{
var z = GetSquaredDerectionField(img, Sigma1);
var kernel2 =
KernelHelper.MakeComplexKernel((x, y) => Gaussian.Gaussian2D(x, y, Sigma2) * x / (x == 0 && y == 0 ? 1 : Math.Sqrt(x * x + y * y)),
(x, y) => Gaussian.Gaussian2D(x, y, Sigma2) * y / (x == 0 && y == 0 ? 1 : Math.Sqrt(x * x + y * y)),
KernelHelper.GetKernelSizeForGaussianSigma(Sigma2));
var I20 = ConvolutionHelper.ComplexConvolve(z, kernel2);
return(I20);
}
public static Complex[,] EstimateLS(double[,] l1, double Sigma1, double Sigma2)
{
var kernelX = KernelHelper.MakeKernel((x, y) => Gaussian.Gaussian2D(x, y, Sigma1) * x, KernelHelper.GetKernelSizeForGaussianSigma(Sigma1));
var resultX = ConvolutionHelper.Convolve(l1, kernelX);
var kernelY = KernelHelper.MakeKernel((x, y) => Gaussian.Gaussian2D(x, y, Sigma1) * -y, KernelHelper.GetKernelSizeForGaussianSigma(Sigma1));
var resultY = ConvolutionHelper.Convolve(l1, kernelY);
var preZ = KernelHelper.MakeComplexFromDouble(resultX, resultY);
var z = preZ.Select2D(x => x * x);
var kernel2 = KernelHelper.MakeComplexKernel((x, y) => Gaussian.Gaussian2D(x, y, Sigma2), (x, y) => 0,
KernelHelper.GetKernelSizeForGaussianSigma(Sigma2));
var I20 = ConvolutionHelper.ComplexConvolve(z, kernel2);
var I11 = ConvolutionHelper.Convolve(z.Select2D(x => x.Magnitude), kernel2.Select2D(x => x.Real));
Complex[,] LS = KernelHelper.Zip2D(I20, I11, (x, y) => x / y);
return(LS);
}