原文:
Win8 Metro(C#)数字图像处理--2.59 P分位法图像二值化
[函数名称]
P分位法图像二值化
[算法说明]
所谓P分位法图像分割,就是在知道图像中目标所占的比率Ratio时,循环不同的灰度值对图像进行
分割,并计算对应的目标所占的比率,如果该比率与Ratio的差值足够小,那么该阈值就是所求的最
佳分割阈值。
/// <summary> /// P-Parameter method of image segmention. /// </summary> /// <param name="src">The source image.</param> /// <param name="P">The ratio of object, from 0 to 1.</param> /// <returns></returns> public static WriteableBitmap PParameterThSegment(WriteableBitmap src,double P) ////P参数法阈值分割 { if (src != null) { int w = src.PixelWidth; int h = src.PixelHeight; WriteableBitmap dstImage = new WriteableBitmap(w, h); byte[] temp = src.PixelBuffer.ToArray(); byte[] tempMask = (byte[])temp.Clone(); //定义灰度图像信息存储变量 int[] srcData = new int[w * h]; //定义背景和目标像素个数变量 int C1 = 0, C2 = 0; //定义阈值变量 int Th = 0; for (int j = 0; j < h; j++) { for (int i = 0; i < w; i++) { srcData[i + j * w] = (int)((double)tempMask[i * 4 + j * w * 4] * 0.114 + (double)tempMask[i * 4 + 1 + j * w * 4] * 0.587 + (double)tempMask[i * 4 + 2 + j * w * 4] * 0.299); } } for (int T = 0; T <= 255; T++) { for (int i = 0; i < srcData.Length; i++) { if (srcData[i] > T) { C1++; } else { C2++; } } double t = Math.Abs((double)((double)C1 / ((double)C1 + (double)C2)) - P); if (t < 0.01) { Th = T; break; } C1 = 0; C2 = 0; } for (int j = 0; j < h; j++) { for (int i = 0; i < w; i++) { temp[i * 4 + j * w * 4] = temp[i * 4 + 1 + j * w * 4] = temp[i * 4 + 2 + j * w * 4] = (byte)(srcData[i + j * w] < Th ? 0 : 255); } } Stream sTemp = dstImage.PixelBuffer.AsStream(); sTemp.Seek(0, SeekOrigin.Begin); sTemp.Write(temp, 0, w * 4 * h); return dstImage; } else { return null; } }