C#简单数字图像处理程序

using System;using System.Collections.Generic;using System.ComponentModel;using System.Data;using System.Drawing;using System.Drawing.Imaging;using System.Linq;using System.Text;using System.Windows.Forms;  namespace text1{ public partial class ImageEnhancement : Form { public ImageEnhancement() {  InitializeComponent(); } Bitmap bitmap; int iw, ih;  //打开文件 private void 打开ToolStripMenuItem_Click(object sender, EventArgs e) {  pictureBox1.Image = null;//先设置两个picturebox为空  pictureBox2.Image = null;  //使用 OpenFileDialog类打开图片  OpenFileDialog open = new OpenFileDialog();  open.Filter = "图像文件(*.bmp;*.jpg;*gif;*png;*.tif;*.wmf)|"   + "*.bmp;*jpg;*gif;*png;*.tif;*.wmf";  if (open.ShowDialog() == DialogResult.OK)  {  try  {   bitmap = (Bitmap)Image.FromFile(open.FileName);  }  catch (Exception exp) { MessageBox.Show(exp.Message); }  pictureBox1.Refresh();  pictureBox1.Image = bitmap;   label6.Text = "原图";  iw = bitmap.Width;  ih = bitmap.Height;     } } //保存文件 private void 保存ToolStripMenuItem_Click(object sender, EventArgs e) {  string str;  SaveFileDialog saveFileDialog1 = new SaveFileDialog();  saveFileDialog1.Filter = "图像文件(*.BMP)|*.BMP|All File(*.*)|*.*";  saveFileDialog1.ShowDialog();  str = saveFileDialog1.FileName;  pictureBox2.Image.Save(str);   } //退出 private void 退出ToolStripMenuItem_Click(object sender, EventArgs e) {  this.Close(); } private void label5_Click(object sender, EventArgs e) { } //读取灰度值及坐标 private void pictureBox1_MouseDown(object sender, MouseEventArgs e) {  Color pointRGB = bitmap.GetPixel(e.X, e.Y);  textBox1.Text = pointRGB.R.ToString();  textBox2.Text = pointRGB.G.ToString();  textBox3.Text = pointRGB.B.ToString();  textBox4.Text = e.X.ToString();  textBox5.Text = e.Y.ToString();  int a = int.Parse(textBox1.Text); } //线性变换部分 private void linearPO_Click(object sender, EventArgs e) {  if (bitmap != null)  {  linearPOForm linearForm = new linearPOForm();  if (linearForm.ShowDialog() == DialogResult.OK)  {   Rectangle rect = new Rectangle(0, 0, bitmap.Width, bitmap.Height);   System.Drawing.Imaging.BitmapData bmpData = bitmap.LockBits(rect,   System.Drawing.Imaging.ImageLockMode.ReadWrite,   bitmap.PixelFormat);   IntPtr ptr = bmpData.Scan0;   //int bytes = bitmap.Width *;  }  } } private void textBox4_TextChanged(object sender, EventArgs e) { } private void label3_Click(object sender, EventArgs e) { } //对比度扩展 private void 对比度扩展ToolStripMenuItem_Click(object sender, EventArgs e) {  if (bitmap != null)  {  strechDialog dialog = new strechDialog();    if (dialog.ShowDialog() == DialogResult.OK)  {   this.Text = " 图像增强 对比度扩展 ";   Bitmap bm = new Bitmap(pictureBox1.Image);     int x1 = Convert.ToInt32(dialog.getX01);   int y1 = Convert.ToInt32(dialog.getY01);   int x2 = Convert.ToInt32(dialog.getX02);   int y2 = Convert.ToInt32(dialog.getY02);     //计算灰度映射表   int[] pixMap = pixelsMap(x1, y1, x2, y2);     //线性拉伸   bm = stretch(bm, pixMap, iw, ih);     pictureBox2.Refresh();   pictureBox2.Image = bm;   label7.Text = "对比度扩展结果";  }  } }  //计算灰度映射表 public int[] pixelsMap(int x1, int y1, int x2, int y2) {  int[] pMap = new int[256];  //映射表  if (x1 > 0)  {  double k1 = y1 / x1;  //第1段斜率k1  //按第1段斜率k1线性变换  for (int i = 0; i <= x1; i++)   pMap[i] = (int)(k1 * i);  }  double k2 = (y2 - y1) / (x2 - x1); //第2段斜率k2   //按第2段斜率k2线性变换  for (int i = x1 + 1; i <= x2; i++)  if (x2 != x1)   pMap[i] = y1 + (int)(k2 * (i - x1));  else   pMap[i] = y1;   if (x2 < 255)  {  double k3 = (255 - y2) / (255 - x2);//第2段斜率k2   //按第3段斜率k3线性变换  for (int i = x2 + 1; i < 256; i++)   pMap[i] = y2 + (int)(k3 * (i - x2));  }  return pMap; }  //对比度扩展函数 public Bitmap stretch(Bitmap bm, int[] map, int iw, int ih) {  Color c = new Color();  int r, g, b;  for (int j = 0; j < ih; j++)  {  for (int i = 0; i < iw; i++)  {   c = bm.GetPixel(i, j);   r = map[c.R];   g = map[c.G];   b = map[c.B];   if (r >= 255) r = 255;   if (r < 0) r = 0;   if (g >= 255) g = 255;   if (g < 0) g = 0;   if (b >= 255) b = 255;   if (b < 0) b = 0;   bm.SetPixel(i, j, Color.FromArgb(r, g, b));  }  }  return bm; } private void 直方图均衡化ToolStripMenuItem_Click(object sender, EventArgs e) {  if (bitmap != null)  {  this.Text = " 图像增强 直方图均衡化";  Bitmap bm = new Bitmap(pictureBox1.Image);  //获取直方图  int[] hist = gethist(bm, iw, ih);   //直方图均匀化  bm = histequal(bm, hist, iw, ih);   pictureBox2.Refresh();  pictureBox2.Image = bm;  label7.Text = "直方图均衡化结果";  flag = true;  } } bool flag = false;   //直方图均衡化标志  //显示直方图 private void 显示直方图ToolStripMenuItem_Click(object sender, EventArgs e) {  if (flag)  {  Bitmap b1 = new Bitmap(pictureBox1.Image);  Bitmap b2 = new Bitmap(pictureBox2.Image);   int[] hist1 = gethist(b1, iw, ih);  int[] hist2 = gethist(b2, iw, ih);  drawHist(hist1, hist2);  } }  //获取直方图 public int[] gethist(Bitmap bm, int iw, int ih) {  int[] h = new int[256];  for (int j = 0; j < ih; j++)  {  for (int i = 0; i < iw; i++)  {   int grey = (bm.GetPixel(i, j)).R;   h[grey]++;  }  }  return h; } //直方图均衡化 public Bitmap histequal(Bitmap bm, int[] hist, int iw, int ih) {  Color c = new Color();  double p = (double)255 / (iw * ih);  double[] sum = new double[256];  int[] outg = new int[256];  int r, g, b;  sum[0] = hist[0];  for (int i = 1; i < 256; i++)  sum[i] = sum[i - 1] + hist[i];     //灰度变换:i-->outg[i]   for (int i = 0; i < 256; i++)  outg[i] = (int)(p * sum[i]);   for (int j = 0; j < ih; j++)  {  for (int i = 0; i < iw; i++)  {   r = (bm.GetPixel(i, j)).R;   g = (bm.GetPixel(i, j)).G;   b = (bm.GetPixel(i, j)).B;   c = Color.FromArgb(outg[r], outg[g], outg[b]);   bm.SetPixel(i, j, c);  }  }  return bm; }  public void drawHist(int[] h1, int[] h2) {  //画原图直方图------------------------------------------  Graphics g = pictureBox1.CreateGraphics();  Pen pen1 = new Pen(Color.Blue);  g.Clear(this.BackColor);   //找出最大的数,进行标准化.  int maxn = h1[0];  for (int i = 1; i < 256; i++)  if (maxn < h1[i])   maxn = h1[i];   for (int i = 0; i < 256; i++)  h1[i] = h1[i] * 250 / maxn;   g.FillRectangle(new SolidBrush(Color.White), 0, 0, 255, 255);   pen1.Color = Color.Red;  for (int i = 0; i < 256; i++)  g.DrawLine(pen1, i, 255, i, 255 - h1[i]);   g.DrawString("" + maxn, this.Font, new SolidBrush(Color.Blue), 0, 0);   label6.Text = "原图直方图";   //画均衡化后直方图------------------------------------------  g = pictureBox2.CreateGraphics();  pen1 = new Pen(Color.Blue);  g.Clear(this.BackColor);   //找出最大的数,进行标准化.  maxn = h2[0];  for (int i = 1; i < 256; i++)  if (maxn < h2[i])   maxn = h2[i];   for (int i = 0; i < 256; i++)  h2[i] = h2[i] * 250 / maxn;   g.FillRectangle(new SolidBrush(Color.White), 0, 0, 255, 255);   pen1.Color = Color.Red;  for (int i = 0; i < 256; i++)  g.DrawLine(pen1, i, 255, i, 255 - h2[i]);   g.DrawString("" + maxn, this.Font, new SolidBrush(Color.Blue), 0, 0);  label7.Text = "均衡化后直方图";  flag = false; }  private void 阈值滤波ToolStripMenuItem_Click(object sender, EventArgs e) {  if (bitmap != null)  {  this.Text = "图像增强 阈值滤波";  Bitmap bm = new Bitmap(pictureBox1.Image);  //阈值滤波  bm = threshold(bm, iw, ih);   pictureBox2.Refresh();  pictureBox2.Image = bm;  label7.Text = "阈值滤波结果";  } }   //3×3阈值滤波 public Bitmap threshold(Bitmap bm, int iw, int ih) {  Bitmap obm = new Bitmap(pictureBox1.Image);    int avr,  //灰度平均   sum,  //灰度和  num = 0, //计数器  nT = 4, //计数器阈值  T = 50; //阈值  int pij, pkl, //(i,j),(i+k,j+l)处灰度值  err;  //误差    for (int j = 1; j < ih - 1; j++)  {  for (int i = 1; i < iw - 1; i++)  {   //取3×3块的9个象素, 求和   sum = 0;   for (int k = -1; k < 2; k++)   {   for (int l = -1; l < 2; l++)   {    if ((k != 0) || (l != 0))    {    pkl = (bm.GetPixel(i + k, j + l)).R;    pij = (bm.GetPixel(i, j)).R;    err = Math.Abs(pkl - pij);    sum = sum + pkl;    if (err > T) num++;    }   }   }   avr = (int)(sum / 8.0f);  //平均值   if (num > nT)   obm.SetPixel(i, j, Color.FromArgb(avr, avr, avr));  }  }  return obm; }  private void 均值滤波ToolStripMenuItem_Click(object sender, EventArgs e) {  if (bitmap != null)  {  this.Text = "数字图像处理";  Bitmap bm = new Bitmap(pictureBox1.Image);  bm = average(bm, iw, ih);  pictureBox2.Refresh();  pictureBox2.Image = bm;  label7.Text = "均值滤波结果";  } } //均值滤波 public Bitmap average(Bitmap bm, int iw, int ih) {  Bitmap obm = new Bitmap(pictureBox1.Image);  for (int j = 1; j < ih - 1; j++)  {  for (int i = 1; i < iw - 1; i++)  {   int avr;   int avr1;   int avr2;   int sum = 0;   int sum1 = 0;   int sum2 = 0;   for (int k = -1; k <= 1; k++)   {   for (int l = -1; l <= 1; l++)   {    sum = sum + (bm.GetPixel(i + k, j + 1).R);    sum1 = sum1 + (bm.GetPixel(i + k, j + 1).G);    sum2 = sum2 + (bm.GetPixel(i + k, j + 1).B);   }   }   avr = (int)(sum / 9.0f);   avr1 = (int)(sum1 / 9.0f);   avr2 = (int)(sum2 / 9.0f);   obm.SetPixel(i, j, Color.FromArgb(avr, avr1, avr2));  }  }  return obm; }  private void 中值滤波ToolStripMenuItem_Click(object sender, EventArgs e) {  if (bitmap != null)  {     this.Text = "图像增强 中值滤波";   Bitmap bm = new Bitmap(pictureBox1.Image);   int num =3;   //中值滤波   bm = median(bm, iw, ih, num);    pictureBox2.Refresh();   pictureBox2.Image = bm;   label2.Location = new Point(370, 280);   if (num == 1) label7.Text = "1X5窗口滤波结果";   else if (num == 2) label7.Text = "5X1窗口滤波结果";   else if (num == 3) label7.Text = "5X5窗口滤波结果";    } }  //中值滤波方法 public Bitmap median(Bitmap bm, int iw, int ih, int n) {  Bitmap obm = new Bitmap(pictureBox1.Image);  for (int j = 2; j < ih - 2; j++)  {  int[] dt;  int[] dt1;  int[] dt2;  for (int i = 2; i < iw - 2; i++)  {   int m = 0, r = 0, r1 = 0, r2 = 0, a = 0, b = 0;   if (n == 3)   {   dt = new int[25];   dt1 = new int[25];   dt2 = new int[25];   //取5×5块的25个象素   for (int k = -2; k < 3; k++)   {    for (int l = -2; l < 3; l++)    {    //取(i+k,j+l)处的象素，赋于数组dt    dt[m] = (bm.GetPixel(i + k, j + l)).R;    dt1[a] = (bm.GetPixel(i + k, j + l)).G;    dt2[b] = (bm.GetPixel(i + k, j + l)).B;    m++;    a++;    b++;    }   }   //冒泡排序,输出中值   r = median_sorter(dt, 25); //中值    r1 = median_sorter(dt1, 25);   r2 = median_sorter(dt2, 25);   }   else if (n == 1)   {   dt = new int[5];    //取1×5窗口5个像素   dt[0] = (bm.GetPixel(i, j - 2)).R;   dt[1] = (bm.GetPixel(i, j - 1)).R;   dt[2] = (bm.GetPixel(i, j)).R;   dt[3] = (bm.GetPixel(i, j + 1)).R;   dt[4] = (bm.GetPixel(i, j + 2)).R;   r = median_sorter(dt, 5); //中值   dt1 = new int[5];     //取1×5窗口5个像素   dt1[0] = (bm.GetPixel(i, j - 2)).G;   dt1[1] = (bm.GetPixel(i, j - 1)).G;   dt1[2] = (bm.GetPixel(i, j)).G;   dt1[3] = (bm.GetPixel(i, j + 1)).G;   dt1[4] = (bm.GetPixel(i, j + 2)).G;   r1 = median_sorter(dt1, 5); //中值    dt2 = new int[5];     //取1×5窗口5个像素   dt2[0] = (bm.GetPixel(i, j - 2)).B;   dt2[1] = (bm.GetPixel(i, j - 1)).B;   dt2[2] = (bm.GetPixel(i, j)).B;   dt2[3] = (bm.GetPixel(i, j + 1)).B;   dt2[4] = (bm.GetPixel(i, j + 2)).B;   r2 = median_sorter(dt2, 5); //中值       }   else if (n == 2)   {   dt = new int[5];     //取5×1窗口5个像素   dt[0] = (bm.GetPixel(i - 2, j)).R;   dt[1] = (bm.GetPixel(i - 1, j)).R;   dt[2] = (bm.GetPixel(i, j)).R;   dt[3] = (bm.GetPixel(i + 1, j)).R;   dt[4] = (bm.GetPixel(i + 2, j)).R;   r = median_sorter(dt, 5); //中值 dt = new int[5];     //取5×1窗口5个像素   dt1 = new int[5];   dt1[0] = (bm.GetPixel(i - 2, j)).G;   dt1[1] = (bm.GetPixel(i - 1, j)).G;   dt1[2] = (bm.GetPixel(i, j)).G;   dt1[3] = (bm.GetPixel(i + 1, j)).G;   dt1[4] = (bm.GetPixel(i + 2, j)).G;   r1 = median_sorter(dt1, 5); //中值     //取5×1窗口5个像素   dt2 = new int[5];   dt2[0] = (bm.GetPixel(i - 2, j)).B;   dt2[1] = (bm.GetPixel(i - 1, j)).B;   dt2[2] = (bm.GetPixel(i, j)).B;   dt2[3] = (bm.GetPixel(i + 1, j)).B;   dt2[4] = (bm.GetPixel(i + 2, j)).B;   r2 = median_sorter(dt2, 5); //中值     }   obm.SetPixel(i, j, Color.FromArgb(r, r1, r2));  //输出     }  }  return obm; } //冒泡排序,输出中值 public int median_sorter(int[] dt, int m) {  int tem;  for (int k = m - 1; k >= 1; k--)  for (int l = 1; l <= k; l++)   if (dt[l - 1] > dt[l])   {   tem = dt[l];   dt[l] = dt[l - 1];   dt[l - 1] = tem;   }  return dt[(int)(m / 2)]; } private void pictureBox1_Click(object sender, EventArgs e) { }   private void 图像锐化ToolStripMenuItem_Click(object sender, EventArgs e) {  }   /*   * pix --待检测图像数组  * iw, ih --待检测图像宽高  * num --算子代号.1:Kirsch算子;2:Laplace算子;3:Prewitt算子;5:Sobel算子 */ public Bitmap detect(Bitmap bm, int iw, int ih, int num)  {   Bitmap b1 = new Bitmap(pictureBox1.Image);   Color c = new Color();  int i, j, r;  int[,] inr = new int[iw, ih]; //红色分量矩阵  int[,] ing = new int[iw, ih]; //绿色分量矩阵  int[,] inb = new int[iw, ih]; //蓝色分量矩阵  int[,] gray = new int[iw, ih];//灰度图像矩阵    //转变为灰度图像矩阵   for (j = 0; j < ih; j++)  {  for (i = 0; i < iw; i++)  {   c = bm.GetPixel(i, j);   inr[i, j] = c.R;   ing[i, j] = c.G;   inb[i, j] = c.B;   gray[i, j] = (int)((c.R + c.G + c.B) / 3.0);  }  }  if (num == 1)//Kirsch  {  int[,] kir0 = {{ 5, 5, 5},    {-3, 0,-3},    {-3,-3,-3}},//kir0    kir1 = {{-3, 5, 5},    {-3, 0, 5},    {-3,-3,-3}},//kir1    kir2 = {{-3,-3, 5},    {-3, 0, 5},    {-3,-3, 5}},//kir2    kir3 = {{-3,-3,-3},    {-3, 0, 5},    {-3, 5, 5}},//kir3    kir4 = {{-3,-3,-3},    {-3, 0,-3},    { 5, 5, 5}},//kir4    kir5 = {{-3,-3,-3},    { 5, 0,-3},    { 5, 5,-3}},//kir5    kir6 = {{ 5,-3,-3},    { 5, 0,-3},    { 5,-3,-3}},//kir6    kir7 = {{ 5, 5,-3},    { 5, 0,-3},    {-3,-3,-3}};//kir7   //边缘检测   int[,] edge0 = new int[iw, ih];   int[,] edge1 = new int[iw, ih];   int[,] edge2 = new int[iw, ih];   int[,] edge3 = new int[iw, ih];   int[,] edge4 = new int[iw, ih];   int[,] edge5 = new int[iw, ih];   int[,] edge6 = new int[iw, ih];   int[,] edge7 = new int[iw, ih];   edge0 = edgeEnhance(gray, kir0, iw, ih);  edge1 = edgeEnhance(gray, kir1, iw, ih);  edge2 = edgeEnhance(gray, kir2, iw, ih);  edge3 = edgeEnhance(gray, kir3, iw, ih);  edge4 = edgeEnhance(gray, kir4, iw, ih);  edge5 = edgeEnhance(gray, kir5, iw, ih);  edge6 = edgeEnhance(gray, kir6, iw, ih);  edge7 = edgeEnhance(gray, kir7, iw, ih);   int[] tem = new int[8];  int max;  for (j = 0; j < ih; j++)  {   for (i = 0; i < iw; i++)   {   tem[0] = edge0[i, j];   tem[1] = edge1[i, j];   tem[2] = edge2[i, j];   tem[3] = edge3[i, j];   tem[4] = edge4[i, j];   tem[5] = edge5[i, j];   tem[6] = edge6[i, j];   tem[7] = edge7[i, j];   max = 0;   for (int k = 0; k < 8; k++)    if (tem[k] > max) max = tem[k];   if (max > 255) max = 255;   r = 255 - max;   b1.SetPixel(i, j, Color.FromArgb(r, r, r));   }  }  }  else if (num == 2)   //Laplace  {  int[,] lap1 = {{ 1, 1, 1},    { 1,-8, 1},    { 1, 1, 1}};   /*byte[][] lap2 = {{ 0, 1, 0},     { 1,-4, 1},     { 0, 1, 0}}; */   //边缘增强  int[,] edge = edgeEnhance(gray, lap1, iw, ih);   for (j = 0; j < ih; j++)  {   for (i = 0; i < iw; i++)   {   r = edge[i, j];   if (r > 255) r = 255;    if (r < 0) r = 0;   c = Color.FromArgb(r, r, r);   b1.SetPixel(i, j, c);   }  }  }  else if (num == 3)//Prewitt  {  //Prewitt算子D_x模板  int[,] pre1 = {{ 1, 0,-1},    { 1, 0,-1},    { 1, 0,-1}};   //Prewitt算子D_y模板  int[,] pre2 = {{ 1, 1, 1},    { 0, 0, 0},    {-1,-1,-1}};  int[,] edge1 = edgeEnhance(gray, pre1, iw, ih);    int[,] edge2 = edgeEnhance(gray, pre2, iw, ih);  for (j = 0; j < ih; j++)  {   for (i = 0; i < iw; i++)   {   r = Math.Max(edge1[i, j], edge2[i, j]);      if(r > 255) r = 255;   c = Color.FromArgb(r, r, r);   b1.SetPixel(i, j, c);   }  }  }   else if (num == 5)    //Sobel  {  int[,] sob1 = {{ 1, 0,-1},    { 2, 0,-2},    { 1, 0,-1}};  int[,] sob2 = {{ 1, 2, 1},    { 0, 0, 0},    {-1,-2,-1}},   int[,] edge1 = edgeEnhance(gray, sob1, iw, ih);  int[,] edge2 = edgeEnhance(gray, sob2, iw, ih);  for (j = 0; j < ih; j++)  {   for (i = 0; i < iw; i++)   {   r = Math.Max(edge1[i, j], edge2[i, j]);   if(r > 255) r = 255;   c = Color.FromArgb(r, r, r);   b1.SetPixel(i, j, c);   }  }  }  return b1; } private void kirsch算子锐化ToolStripMenuItem_Click(object sender, EventArgs e) {  if (bitmap != null)  {  // this.Text = " 图像 - 图像锐化 - Kirsch算子";  Bitmap bm = new Bitmap(pictureBox1.Image);  //1: Kirsch锐化  bm = detect(bm, iw, ih, 1)  pictureBox2.Refresh();  pictureBox2.Image = bm;  label7.Text = " Kirsch算子 锐化结果";  } } public int[,] edgeEnhance(int[,] ing, int[,] tmp, int iw, int ih) {  int[,] ed = new int[iw, ih];  for (int j = 1; j < ih - 1; j++)  {  for (int i = 1; i < iw - 1; i++)  {   ed[i, j] = Math.Abs(tmp[0, 0] * ing[i - 1, j - 1]    + tmp[0, 1] * ing[i - 1, j] + tmp[0, 2] * ing[i - 1, j + 1]    + tmp[1, 0] * ing[i, j - 1] + tmp[1, 1] * ing[i, j]    + tmp[1, 2] * ing[i, j + 1] + tmp[2, 0] * ing[i + 1, j - 1]    + tmp[2, 1] * ing[i + 1, j] + tmp[2, 2] * ing[i + 1, j + 1]);  }  }  return ed; } //Laplace算子 private void laplace算子锐化ToolStripMenuItem_Click(object sender, EventArgs e) {  if (bitmap != null)  {   Bitmap bm = new Bitmap(pictureBox1.Image);   //2: Laplace锐化   bm = detect(bm, iw, ih, 2);  pictureBox2.Refresh();  pictureBox2.Image = bm;  label7.Text = "Laplace算子 锐化结果";  } }  //Prewitt算子 private void prewitt算子锐化ToolStripMenuItem_Click(object sender, EventArgs e) {  if (bitmap != null)  {    Bitmap bm = new Bitmap(pictureBox1.Image);  //3:Prewitt锐化  bm = detect(bm, iw, ih, 3);  pictureBox2.Refresh();  pictureBox2.Image = bm;  label2.Location = new Point(390, 280);  label7.Text = " Prewitt算子 锐化结果";  } }   //Roberts算子 private void roberts算子锐化ToolStripMenuItem_Click(object sender, EventArgs e) {  if (bitmap != null)  {  Bitmap bm = new Bitmap(pictureBox1.Image);  //Robert边缘检测   bm = robert(bm, iw, ih);  pictureBox2.Refresh();  pictureBox2.Image = bm;  label2.Location = new Point(390, 280);  label7.Text = "Roberts算子 锐化结果";  } }  //roberts算法 public Bitmap robert(Bitmap bm, int iw, int ih) {  int r, r0, r1, r2, r3, g, g0, g1, g2, g3, b, b0, b1, b2, b3;  Bitmap obm = new Bitmap(pictureBox1.Image);  int[,] inr = new int[iw, ih];//红色分量矩阵  int[,] ing = new int[iw, ih];//绿色分量矩阵  int[,] inb = new int[iw, ih];//蓝色分量矩阵  int[,] gray = new int[iw, ih];//灰度图像矩阵     for (int j = 1; j < ih - 1; j++)  {  for (int i = 1; i < iw - 1; i++)  {   r0 = (bm.GetPixel(i, j)).R;   r1 = (bm.GetPixel(i, j + 1)).R;   r2 = (bm.GetPixel(i + 1, j)).R;   r3 = (bm.GetPixel(i + 1, j + 1)).R;      r = (int)Math.Sqrt((r0 - r3) * (r0 - r3) + (r1 - r2) * (r1 - r2));    g0 = (bm.GetPixel(i, j)).G;   g1 = (bm.GetPixel(i, j + 1)).G;   g2 = (bm.GetPixel(i + 1, j)).G;   g3 = (bm.GetPixel(i + 1, j + 1)).G;   g = (int)Math.Sqrt((g0 - g3) * (g0 - g3) + (g1 - g2) * (g1 - g2));    b0 = (bm.GetPixel(i, j)).B;   b1 = (bm.GetPixel(i, j + 1)).B;   b2 = (bm.GetPixel(i + 1, j)).B;   b3 = (bm.GetPixel(i + 1, j + 1)).B;   b = (int)Math.Sqrt((b0 - b3) * (b0 - b3)   + (b1 - b2) * (b1 - b2));    if (r < 0)   r = 0;     //黑色，边缘点   if (r > 255)   r = 255;    obm.SetPixel(i, j, Color.FromArgb(r, r, r));  }  }  return obm; } //Sobel算子 private void sobel算子锐化ToolStripMenuItem_Click(object sender, EventArgs e) {  if (bitmap != null)  {  Bitmap bm = new Bitmap(pictureBox1.Image);  //5: Sobel锐化  bm = detect(bm, 256, 256, 5);   pictureBox2.Refresh();  pictureBox2.Image = bm;   label7.Text = " Sobel算子 锐化结果";  } }  private void 低通滤波ToolStripMenuItem_Click(object sender, EventArgs e) {  if (bitmap != null)  {  Bitmap bm = new Bitmap(pictureBox1.Image);  int num ;  for (num = 1; num < 4; num++)  {   //低通滤波   bm = lowpass(bm, iw, ih, num);    pictureBox2.Refresh();   pictureBox2.Image = bm;    if (num == 1) label7.Text = "1*5模板低通滤波结果";   else if (num == 2) label7.Text = "5*1模板低通滤波结果";   else if (num == 3) label7.Text = "5*5模板低通滤波结果";  }  }   } //3×3低通滤波方法 public Bitmap lowpass(Bitmap bm, int iw, int ih, int n) {  Bitmap obm = new Bitmap(pictureBox1.Image);  int[,] h;   //定义扩展输入图像矩阵  int[,] ex_inpix = exinpix(bm, iw, ih);   //低通滤波  for (int j = 1; j < ih + 1; j++)  {  for (int i = 1; i < iw + 1; i++)  {   int r = 0, sum = 0;    //低通模板    h = low_matrix(n);    //求3×3窗口9个像素加权和   for (int k = -1; k < 2; k++)   for (int l = -1; l < 2; l++)    sum = sum + h[k + 1, l + 1] * ex_inpix[i + k, j + l];    if (n == 1)   r = (int)(sum / 9); //h1平均值   else if (n == 2)   r = (int)(sum / 10); //h2   else if (n == 3)   r = (int)(sum / 16); //h3    obm.SetPixel(i - 1, j - 1, Color.FromArgb(r, r, r)); //输出     }  }  return obm; } //定义扩展输入图像矩阵 public int[,] exinpix(Bitmap bm, int iw, int ih) {  int[,] ex_inpix = new int[iw + 2, ih + 2];  //获取非边界灰度值  for (int j = 0; j < ih; j++)  for (int i = 0; i < iw; i++)   ex_inpix[i + 1, j + 1] = (bm.GetPixel(i, j)).R;  //四角点处理  ex_inpix[0, 0] = ex_inpix[1, 1];  ex_inpix[0, ih + 1] = ex_inpix[1, ih];  ex_inpix[iw + 1, 0] = ex_inpix[iw, 1];  ex_inpix[iw + 1, ih + 1] = ex_inpix[iw, ih];  //上下边界处理  for (int j = 1; j < ih + 1; j++)  {  ex_inpix[0, j] = ex_inpix[1, j]; //上边界   ex_inpix[iw + 1, j] = ex_inpix[iw, j];//下边界  } //左右边界处理  for (int i = 1; i < iw + 1; i++)  {  ex_inpix[i, 0] = ex_inpix[i, 1]; //左边界   ex_inpix[i, ih + 1] = ex_inpix[i, ih];//右边界  }  return ex_inpix; } //低通滤波模板 public int[,] low_matrix(int n) {  int[,] h = new int[3, 3];  if (n == 1) //h1  {  h[0, 0] = 1; h[0, 1] = 1; h[0, 2] = 1;  h[1, 0] = 1; h[1, 1] = 1; h[1, 2] = 1;  h[2, 0] = 1; h[2, 1] = 1; h[2, 2] = 1;  }  else if (n == 2)//h2  {  h[0, 0] = 1; h[0, 1] = 1; h[0, 2] = 1;  h[1, 0] = 1; h[1, 1] = 2; h[1, 2] = 1;  h[2, 0] = 1; h[2, 1] = 1; h[2, 2] = 1;  }  else if (n == 3)//h3  {  h[0, 0] = 1; h[0, 1] = 2; h[0, 2] = 1;  h[1, 0] = 2; h[1, 1] = 4; h[1, 2] = 2;  h[2, 0] = 1; h[2, 1] = 2; h[2, 2] = 1;  }  return h; }  }}