using System;using System.Collections.Generic;using System.Drawing;using System.Linq;using System.Text;using System.Threading.Tasks;namespace CommonHelper{    /// <summary>    /// 高斯模糊算法    /// </summary>    public class GaussianHelper    {        public static double[,] Calculate1DSampleKernel(double deviation, int size)        {            double[,] ret = new double[size, 1];            double sum = 0;            int half = size / 2;            for (int i = 0; i < size; i++)            {                ret[i, 0] = 1 / (Math.Sqrt(2 * Math.PI) * deviation) * Math.Exp(-(i - half) * (i - half) / (2 * deviation * deviation));                sum += ret[i, 0];            }            return ret;        }        public static double[,] Calculate1DSampleKernel(double deviation)        {            int size = (int)Math.Ceiling(deviation * 3) * 2 + 1;            return Calculate1DSampleKernel(deviation, size);        }        public static double[,] CalculateNormalized1DSampleKernel(double deviation)        {            return CalculateNormalized1DSampleKernel(deviation);        }        public static double[,] NormalizeMatrix(double[,] matrix)        {            double[,] ret = new double[matrix.GetLength(0), matrix.GetLength(1)];            double sum = 0;            for (int i = 0; i < ret.GetLength(0); i++)            {                for (int j = 0; j < ret.GetLength(1); j++)                    ret[i, j] = matrix[i, j] / sum;            }            return ret;        }        public static double[,] GaussianConvolution(double[,] matrix, double deviation)        {            double[,] kernel = CalculateNormalized1DSampleKernel(deviation);            double[,] res1 = new double[matrix.GetLength(0), matrix.GetLength(1)];            double[,] res2 = new double[matrix.GetLength(0), matrix.GetLength(1)];            //x-direction            for (int i = 0; i < matrix.GetLength(0); i++)            {                for (int j = 0; j < matrix.GetLength(1); j++)                    res1[i, j] = PRocessPoint(matrix, i, j, kernel, 0);            }            //y-direction            for (int i = 0; i < matrix.GetLength(0); i++)            {                for (int j = 0; j < matrix.GetLength(1); j++)                    res2[i, j] = processPoint(matrix, i, j, kernel, 0);            }            return res2;        }        private static double processPoint(double[,] matrix, int x, int y, double[,] kernel, int direction)        {            double res = 0;            int half = kernel.GetLength(0) / 2;            for (int i = 0; i < kernel.GetLength(0); i++)            {                int cox = direction == 0 ? x + i - half : x;                int coy = direction == 0 ? y + i - half : y;                if (cox >= 0 && cox < matrix.GetLength(0) && coy >= 0 && coy < matrix.GetLength(1))                    res += matrix[cox, coy] * kernel[i, 0];            }            return res;        }        /// <summary>        /// 對顏色值進行灰色處理        /// </summary>        /// <param name="cr"></param>        /// <returns></returns>        private Color grayscale(Color cr)        {             return Color.FromArgb(cr.A,(int)(cr.R*.3+cr.G*.59+cr.B*0.11),                (int)(cr.R*.3+cr.G*.59+cr.B*0.11),                    (int)(cr.R*.3+cr.G*.59+cr.B*0.11));        }        /// <summary>        /// 對圖片進行高斯模糊        /// </summary>        /// <param name="d"></param>        /// <param name="image"></param>        /// <returns></returns>        public Bitmap FilterProcessImage(double d, Bitmap image)        {            Bitmap ret = new Bitmap(image.Width, image.Height);            Double[,] matrixR = new Double[image.Width, image.Height];            Double[,] matrixG = new Double[image.Width, image.Height];            Double[,] matrixB = new Double[image.Width, image.Height];            for (int i = 0; i < image.Width; i++)            {                for (int j = 0; j < image.Height; j++)                {                    matrixR[i, j] = image.GetPixel(i, j).R;                    matrixG[i, j] = image.GetPixel(i, j).G;                    matrixB[i, j] = image.GetPixel(i, j).B;                }            }            matrixR = GaussianHelper.GaussianConvolution(matrixR, d);            matrixG = GaussianHelper.GaussianConvolution(matrixG, d);            matrixB = GaussianHelper.GaussianConvolution(matrixB, d);            for (int i = 0; i < image.Width; i++)            {                for (int j = 0; j < image.Height; j++)                {                    Int32 R = (int)Math.Min(255, matrixR[i, j]);                    Int32 G = (int)Math.Min(255, matrixG[i, j]);                    Int32 B = (int)Math.Min(255, matrixB[i, j]);                    ret.SetPixel(i,j,Color.FromArgb(R,G,B));                }            }            return ret;        }    }}