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時間︰2018-09-27 15:28:13 編輯︰豬哥 來源︰轉載

C#編寫的簡單數字圖像處理程序,數字圖像處理的平時成績和編程作業竟然佔50%,那就把最近做的事寫個札記吧。

先放個最終做成提交的效果看看︰

C#簡單數字圖像處理程序

1.直方圖均衡化

C#簡單數字圖像處理程序

2.算子銳化

C#簡單數字圖像處理程序

C#簡單數字圖像處理程序

C#簡單數字圖像處理程序

3.空域增強

C#簡單數字圖像處理程序

C#簡單數字圖像處理程序

C#簡單數字圖像處理程序

C#簡單數字圖像處理程序

一、要達到的目的和效果

  1.打開,保存圖片;

  2.獲取圖像灰度值,圖像坐標;

  3.進行線性變換,直方圖均衡化處理;

  4.直方圖變換增強,以及各種濾波處理;

  5.圖像銳化(Kirsch,Laplace,sobel等算子)。

二、編程環境及語言

C#-WindowsForm-VS2015

三、圖標

最近發現了一個完全免費的矢量圖標網站阿里媽媽iconfont,超級好用。

C#簡單數字圖像處理程序

當然也可以自己動手畫一個

四、創建窗體

  1.先建一個C#Windows窗體應用程序,設置好保存路徑和項目名稱;

  2.打開工具箱,找到menuscript,加到窗體中,依次填寫菜單以及子菜單的名稱,菜單里將完成主要的圖像處理操作;

  3.因為要顯示處理前後的圖片,所以再添加兩個picturebox控件,可以設置停靠模式為stretchImage;再加兩個groupbox,每個groupbox里添加label和textbox控件,用來顯示圖像灰度值及坐標,這樣窗體基本搭建完成,還是挺簡單的。

五、主要代碼

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; 
 //打開文件
 private void 打開ToolStripMenuItem_Click(object sender, EventArgs e)
 {
  pictureBox1.Image = null;//先設置兩個picturebox為空
  pictureBox2.Image = null;
  //使用 OpenFileDialog類打開圖片
  OpenFileDialog open = new OpenFileDialog();
  open.Filter = "圖像文件(*.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 = "原圖";
  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 = "圖像文件(*.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)
 {
 }
 //讀取灰度值及坐標
 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);
 }
 //線性變換部分
 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)
 {
 }
 //對比度擴展
 private void 對比度擴展ToolStripMenuItem_Click(object sender, EventArgs e)
 {
  if (bitmap != null)
  {
  strechDialog dialog = new strechDialog();
 
 
  if (dialog.ShowDialog() == DialogResult.OK)
  {
   this.Text = " 圖像增強 對比度擴展 ";
   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);
 
 
   //計算灰度映射表
   int[] pixMap = pixelsMap(x1, y1, x2, y2);
 
 
   //線性拉伸
   bm = stretch(bm, pixMap, iw, ih);
 
 
   pictureBox2.Refresh();
   pictureBox2.Image = bm;
   label7.Text = "對比度擴展結果";
  }
  }
 }
 
 //計算灰度映射表
 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線性變換
  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線性變換
  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線性變換
  for (int i = x2 + 1; i < 256; i++)
   pMap[i] = y2 + (int)(k3 * (i - x2));
  }
  return pMap;
 }
 
 //對比度擴展函數
 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 直方圖均衡化ToolStripMenuItem_Click(object sender, EventArgs e)
 {
  if (bitmap != null)
  {
  this.Text = " 圖像增強 直方圖均衡化";
  Bitmap bm = new Bitmap(pictureBox1.Image);
  //獲取直方圖
  int[] hist = gethist(bm, iw, ih);
 
  //直方圖均勻化
  bm = histequal(bm, hist, iw, ih);
 
  pictureBox2.Refresh();
  pictureBox2.Image = bm;
  label7.Text = "直方圖均衡化結果";
  flag = true;
  }
 }
 bool flag = false;   //直方圖均衡化標志
 
 //顯示直方圖
 private void 顯示直方圖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);
  }
 }
 
 //獲取直方圖
 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;
 }
 //直方圖均衡化
 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];
 
 
 
  //灰度變換: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)
 {
  //畫原圖直方圖------------------------------------------
  Graphics g = pictureBox1.CreateGraphics();
  Pen pen1 = new Pen(Color.Blue);
  g.Clear(this.BackColor);
 
  //找出最大的數,進行標準化.
  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 = "原圖直方圖";
 
  //畫均衡化後直方圖------------------------------------------
  g = pictureBox2.CreateGraphics();
  pen1 = new Pen(Color.Blue);
  g.Clear(this.BackColor);
 
  //找出最大的數,進行標準化.
  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 = "均衡化後直方圖";
  flag = false;
 }
 
 private void 閾值濾波ToolStripMenuItem_Click(object sender, EventArgs e)
 {
  if (bitmap != null)
  {
  this.Text = "圖像增強 閾值濾波";
  Bitmap bm = new Bitmap(pictureBox1.Image);
  //閾值濾波
  bm = threshold(bm, iw, ih);
 
  pictureBox2.Refresh();
  pictureBox2.Image = bm;
  label7.Text = "閾值濾波結果";
  }
 }
 
 
 //3×3閾值濾波
 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, //計數器
  nT = 4, //計數器閾值
  T = 50; //閾值
  int pij, pkl, //(i,j),(i+k,j+l)處灰度值
  err;  //誤差
 
 
  for (int j = 1; j < ih - 1; j++)
  {
  for (int i = 1; i < iw - 1; i++)
  {
   //取3×3塊的9個象素, 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 均值濾波ToolStripMenuItem_Click(object sender, EventArgs e)
 {
  if (bitmap != null)
  {
  this.Text = "數字圖像處理";
  Bitmap bm = new Bitmap(pictureBox1.Image);
  bm = average(bm, iw, ih);
  pictureBox2.Refresh();
  pictureBox2.Image = bm;
  label7.Text = "均值濾波結果";
  }
 }
 //均值濾波
 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 中值濾波ToolStripMenuItem_Click(object sender, EventArgs e)
 {
  if (bitmap != null)
  {
  
   this.Text = "圖像增強 中值濾波";
   Bitmap bm = new Bitmap(pictureBox1.Image);
   int num =3;
   //中值濾波
   bm = median(bm, iw, ih, num);
 
   pictureBox2.Refresh();
   pictureBox2.Image = bm;
   label2.Location = new Point(370, 280);
   if (num == 1) label7.Text = "1X5窗口濾波結果";
   else if (num == 2) label7.Text = "5X1窗口濾波結果";
   else if (num == 3) label7.Text = "5X5窗口濾波結果";
  
  }
 }
 
 //中值濾波方法
 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塊的25個象素
   for (int k = -2; k < 3; k++)
   {
    for (int l = -2; l < 3; l++)
    {
    //取(i+k,j+l)處的象素,賦于數組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,輸出中值
   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個像素
   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個像素
   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個像素
   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個像素
   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個像素
   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個像素
   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));  //輸出   
  }
  }
  return obm;
 }
 //冒泡排序,輸出中值
 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 圖像銳化ToolStripMenuItem_Click(object sender, EventArgs e)
 {
  }
 
 
 /* 
  * pix --待檢測圖像數組
  * iw, ih --待檢測圖像寬高
  * num --算子代號.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]; //紅色分量矩陣
  int[,] ing = new int[iw, ih]; //綠色分量矩陣
  int[,] inb = new int[iw, ih]; //藍色分量矩陣
  int[,] gray = new int[iw, ih];//灰度圖像矩陣 
 
  //轉變為灰度圖像矩陣
 
  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 
  //邊緣檢測
 
  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}}; */
 
  //邊緣增強
  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算子銳化ToolStripMenuItem_Click(object sender, EventArgs e)
 {
  if (bitmap != null)
  {
  // this.Text = " 圖像 - 圖像銳化 - Kirsch算子";
  Bitmap bm = new Bitmap(pictureBox1.Image);
  //1: Kirsch銳化
  bm = detect(bm, iw, ih, 1)
  pictureBox2.Refresh();
  pictureBox2.Image = bm;
  label7.Text = " Kirsch算子 銳化結果";
  }
 }
 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算子銳化ToolStripMenuItem_Click(object sender, EventArgs e)
 {
  if (bitmap != null)
  { 
  Bitmap bm = new Bitmap(pictureBox1.Image);
 
  //2: Laplace銳化 
  bm = detect(bm, iw, ih, 2);
  pictureBox2.Refresh();
  pictureBox2.Image = bm;
  label7.Text = "Laplace算子 銳化結果";
  }
 }
 
 //Prewitt算子
 private void prewitt算子銳化ToolStripMenuItem_Click(object sender, EventArgs e)
 {
  if (bitmap != null)
  {
  
  Bitmap bm = new Bitmap(pictureBox1.Image);
  //3:Prewitt銳化
  bm = detect(bm, iw, ih, 3);
  pictureBox2.Refresh();
  pictureBox2.Image = bm;
  label2.Location = new Point(390, 280);
  label7.Text = " Prewitt算子 銳化結果";
  }
 }
 
 
 //Roberts算子
 private void roberts算子銳化ToolStripMenuItem_Click(object sender, EventArgs e)
 {
  if (bitmap != null)
  {
  Bitmap bm = new Bitmap(pictureBox1.Image);
  //Robert邊緣檢測 
  bm = robert(bm, iw, ih);
  pictureBox2.Refresh();
  pictureBox2.Image = bm;
  label2.Location = new Point(390, 280);
  label7.Text = "Roberts算子 銳化結果";
  }
 }
 
 //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];//紅色分量矩陣
  int[,] ing = new int[iw, ih];//綠色分量矩陣
  int[,] inb = new int[iw, ih];//藍色分量矩陣
  int[,] gray = new int[iw, ih];//灰度圖像矩陣  
 
  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,邊緣點
   if (r > 255)
   r = 255;
 
   obm.SetPixel(i, j, Color.FromArgb(r, r, r));
  }
  }
  return obm;
 }
 //Sobel算子
 private void sobel算子銳化ToolStripMenuItem_Click(object sender, EventArgs e)
 {
  if (bitmap != null)
  {
  Bitmap bm = new Bitmap(pictureBox1.Image);
  //5: Sobel銳化
  bm = detect(bm, 256, 256, 5);
 
  pictureBox2.Refresh();
  pictureBox2.Image = bm;
 
  label7.Text = " Sobel算子 銳化結果";
  }
 }
 
 private void 低通濾波ToolStripMenuItem_Click(object sender, EventArgs e)
 {
  if (bitmap != null)
  {
  Bitmap bm = new Bitmap(pictureBox1.Image);
  int num ;
  for (num = 1; num < 4; num++)
  {
   //低通濾波
   bm = lowpass(bm, iw, ih, num);
 
   pictureBox2.Refresh();
   pictureBox2.Image = bm;
 
   if (num == 1) label7.Text = "1*5模板低通濾波結果";
   else if (num == 2) label7.Text = "5*1模板低通濾波結果";
   else if (num == 3) label7.Text = "5*5模板低通濾波結果";
  }
  }
 
 
 }
 //3×3低通濾波方法
 public Bitmap lowpass(Bitmap bm, int iw, int ih, int n)
 {
  Bitmap obm = new Bitmap(pictureBox1.Image);
  int[,] h;
 
  //定義擴展輸入圖像矩陣
  int[,] ex_inpix = exinpix(bm, iw, ih);
 
  //低通濾波
  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個像素加權和
   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)); //輸出   
  }
  }
  return obm;
 }
 //定義擴展輸入圖像矩陣
 public int[,] exinpix(Bitmap bm, int iw, int ih)
 {
  int[,] ex_inpix = new int[iw + 2, ih + 2];
  //獲取非邊界灰度值
  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;
  //四角點處理
  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];
  //上下邊界處理
  for (int j = 1; j < ih + 1; j++)
  {
  ex_inpix[0, j] = ex_inpix[1, j]; //上邊界 
  ex_inpix[iw + 1, j] = ex_inpix[iw, j];//下邊界
  }
 
//左右邊界處理
  for (int i = 1; i < iw + 1; i++)
  {
  ex_inpix[i, 0] = ex_inpix[i, 1]; //左邊界 
  ex_inpix[i, ih + 1] = ex_inpix[i, ih];//右邊界
  }
  return ex_inpix;
 }
 //低通濾波模板
 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;
 }
 
 }
}

六、參考書籍

《C#數字圖像處理算法典型實例》

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