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); }
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[,] 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); }