GaussianBlur.cs

using System;
 
namespace IdApp.Cv.Transformations.Convolutions
{
    public static partial class ConvolutionOperations
    {
        public static Matrix<float> GaussianBlur(this Matrix<float> M, int KernelWidth)
        {
            return M.Convolute(GaussianBlurKernel(KernelWidth));
        }
 
        public static Matrix<float> GaussianBlur(this Matrix<float> M, int KernelWidth, float Sigma)
        {
            return M.Convolute(GaussianBlurKernel(KernelWidth, Sigma));
        }
 
        public static Matrix<int> GaussianBlur(this Matrix<int> M, int KernelWidth)
        {
            return M.Convolute(GaussianBlurKernel(KernelWidth));
        }
 
        public static Matrix<int> GaussianBlur(this Matrix<int> M, int KernelWidth, float Sigma)
        {
            return M.Convolute(GaussianBlurKernel(KernelWidth, Sigma));
        }
 
        public static IMatrix GaussianBlur(this IMatrix M, int KernelWidth)
        {
            return M.Convolute(GaussianBlurKernel(KernelWidth));
        }
 
        public static IMatrix GaussianBlur(this IMatrix M, int KernelWidth, float Sigma)
        {
            return M.Convolute(GaussianBlurKernel(KernelWidth, Sigma));
        }
 
        public static Matrix<float> GaussianBlurKernel(int KernelWidth)
        {
            return GaussianBlurKernel(KernelWidth, 0.3f * ((KernelWidth - 1) * 0.5f - 1) + 0.8f);
        }
 
        public static Matrix<float> GaussianBlurKernel(int KernelWidth, float Sigma)
        {
            Matrix<float> Kernel = new Matrix<float>(KernelWidth, KernelWidth);
            float d = -(KernelWidth - 1) * 0.5f;
            float x, x2, y, s2;
            int i, j;
 
            s2 = 1.0f / (Sigma * Sigma * 2);
 
            for (i = 0; i < KernelWidth; i++)
            {
                x = i + d;
                x2 = x * x;
 
                for (j = 0; j < KernelWidth; j++)
                {
                    y = j + d;
 
                    Kernel[i, j] = (float)Math.Exp(-(x2 + y * y) * s2);
                }
            }
 
            return Kernel;
        }
 
    }
}