Win8 Metro(C#)数字图像处理--2.55OSTU法图像二值化

原文:Win8 Metro(C#)数字图像处理--2.55OSTU法图像二值化



[函数名称]

Ostu法图像二值化      WriteableBitmap OstuThSegment(WriteableBitmap src)

[函数代码]

        /// <summary>
        /// Ostu method of image segmention.
        /// </summary>
        /// <param name="src">The source image.</param>
        /// <returns></returns>
        public static WriteableBitmap OstuThSegment(WriteableBitmap src) ////Ostu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];
                //定义阈值变量
                int Th = 0; ;
                //定义背景和目标像素数目变量N1,N2，灰度变量U1,U2，灰度和变量Sum1,Sum2，临时缓存变量Temp
                int N1 = 0, N2 = 0, Sum1 = 0, Sum2 = 0;
                //定义背景和目标像素比例变量W1,W2，图像整体平均灰度变量U，方差变量g，对比阈值变量TT
                double W1 = 0, W2 = 0, U1 = 0, U2 = 0, g = 0, TT = 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);
                    }
                }
                //寻找最大类间方差
                for (int T = 0; T <= 255; T++)
                {
                    for (int i = 0; i < srcData.Length; i++)
                    {
                        if (srcData[i] > T)
                        {
                            N2++;
                            Sum2 += srcData[i];
                        }
                        else
                        {
                            N1++;
                            Sum1 += srcData[i];
                        }
                    }
                    W1 = (double)(N1 / (N1 + N2));
                    W2 = (double)(1.0 - W1);
                    U1 = (N1 == 0 ? 0.0 : (Sum1 / N1));
                    U2 = (N2 == 0 ? 0.0 : (Sum2 / N2));
                    g = N1 * N2 * (U1 - U2) * (U1 - U2);
                    if (g > TT)
                    {
                        TT = g;
                        Th = T;
                    }
                    N1 = 0; N2 = 0;
                    Sum1 = 0; Sum2 = 0; W1 = 0.0; W2 = 0.0; U1 = 0.0; U2 = 0.0; g = 0.0;
                }
                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;
            }
        }