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占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：
1.直方圖均衡化
2.算子銳化
3.空域增強
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。
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.因為要顯示處理前后的圖片，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
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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"; //畫均衡化后直方圖------------------------------------------ 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 = "均衡化后直方圖"; 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》
以上就是本文的全部內容，希望對大家的學習有所幫助，也希望大家多多支持服務器之家。
原文鏈接：https://blog.csdn.net/Lynn_whu/article/details/80725831
