WPF：图像处理（四）大津法

[csharp] using System; 
 
namespace Splash.Imaging 
{ 
    /// <summary> 
    /// 图像处理：大津法二值化阈值计算方法 
    /// </summary> 
    public static partial class Binarize 
    { 
        /// <summary> 
        /// 大津法计算阈值 
        /// </summary> 
        /// <param name="grayArray">灰度数组</param> 
        /// <returns>二值化阈值</returns>  
        public static Int32 OtsuThreshold(Byte[,] grayArray) 
        {   // 建立统计直方图 
            Int32[] Histogram = new Int32[256]; 
            Array.Clear(Histogram, 0, 256);     // 初始化 
            foreach (Byte b in grayArray) 
            { 
                Histogram[b]++;                 // 统计直方图 
            } 
 
            // 总的质量矩和图像点数 
            Int32 SumC = grayArray.Length;    // 总的图像点数 
            Double SumU = 0;                  // 双精度避免方差运算中数据溢出 
            for (Int32 i = 1; i < 256; i++) 
            { 
                SumU += i * Histogram[i];     // 总的质量矩                 
            } 
             
            // 灰度区间 
            Int32 MinGrayLevel = Array.FindIndex(Histogram, NonZero);       // 最小灰度值