彻底重写：回到高斯模糊+除法归一化，天然免疫阴影

减法方案(bg-gray)的根本缺陷：阴影处bg被远处亮区域拉高，
差值大，阴影变黑。形态学闭运算核大小两难无解。

除法方案(gray/bg*255)天然免疫阴影：
- 阴影处gray和bg同比例变暗，比值≈1，结果≈255（白色）
- 文字处gray<bg，比值<1，结果<255（偏暗）
- 背景处gray≈bg，比值≈1，结果≈255（白色）

用LUT分段映射增强对比度：0-180压暗（文字变黑），
180-255拉亮（背景变白）。

Co-Authored-By: Claude Opus 4.6 <noreply@anthropic.com>

CamScanner.cs

@@ -322,8 +322,9 @@ public static class DocumentScanner
 
     // ==========================================
     //  第3步：图像增强
-    //  核心：用morphologyEx(CLOSE)做背景估计（比高斯模糊更贴合局部亮度）
-    //  阴影区域的背景估计也低 → bg-gray差值小 → 阴影自然不变黑
+    //  除法归一化：result = (gray / background) * 255
+    //  除法对阴影天然免疫：阴影处gray和bg同比例变暗，比值不变
+    //  高斯模糊做背景估计（不会有底色问题）
     // ==========================================
     private static Mat EnhanceDocument(Mat src)
     {
@@ -331,28 +332,19 @@ public static class DocumentScanner
         Mat gray = new Mat();
         Cv2.CvtColor(src, gray, ColorConversionCodes.BGR2GRAY);
 
-        // --- b: 背景估计（形态学闭运算）---
-        // 闭运算 = 先膨胀后腐蚀，填平暗区域（文字），保留亮区域（背景）
-        // 核要足够大，能完全覆盖文字笔画和行间距，否则文字密集区域背景被拉低
-        // 用多次迭代小核代替单次超大核（性能更好）
-        int morphSize = 41;
-        int iterations = Math.Max(gray.Width, gray.Height) / 200;
-        if (iterations < 3) iterations = 3;
+        // --- b: 背景估计（高斯模糊，大核）---
+        int blurSize = Math.Max(gray.Width, gray.Height) / 8;
+        if (blurSize % 2 == 0) blurSize++;
+        if (blurSize < 51) blurSize = 51;
 
-        Mat morphKernel = Cv2.GetStructuringElement(MorphShapes.Ellipse,
-            new OpenCvSharp.Size(morphSize, morphSize));
         Mat background = new Mat();
-        Cv2.MorphologyEx(gray, background, MorphTypes.Close, morphKernel,
-            null, iterations);
-        morphKernel.Dispose();
+        Cv2.GaussianBlur(gray, background, new OpenCvSharp.Size(blurSize, blurSize), 0);
 
-        // 对背景估计做模糊，消除形态学的块状伪影
-        int smoothSize = morphSize * iterations / 2;
-        if (smoothSize % 2 == 0) smoothSize++;
-        if (smoothSize < 21) smoothSize = 21;
-        Cv2.GaussianBlur(background, background, new OpenCvSharp.Size(smoothSize, smoothSize), 0);
-
-        // --- c: 减法提取墨迹 ---
+        // --- c: 除法归一化 ---
+        // result = (gray / background) * 255
+        // 文字处：gray < bg → 比值 < 1 → 结果 < 255（偏暗）
+        // 背景处：gray ≈ bg → 比值 ≈ 1 → 结果 ≈ 255（白色）
+        // 阴影处：gray和bg同比例变暗 → 比值仍 ≈ 1 → 结果仍 ≈ 255（白色！）
         int w = gray.Width;
         int h = gray.Height;
         byte[] grayData = new byte[w * h];
@@ -362,63 +354,55 @@ public static class DocumentScanner
         Marshal.Copy(background.Data, bgData, 0, bgData.Length);
         background.Dispose();
 
-        // 95百分位数增益
-        int[] inkHist = new int[256];
         for (int i = 0; i < grayData.Length; i++)
         {
-            int ink = bgData[i] - grayData[i];
-            if (ink < 0) ink = 0;
-            if (ink > 255) ink = 255;
-            inkHist[ink]++;
-        }
-        int totalPixels = w * h;
-        int target95 = (int)(totalPixels * 0.95);
-        int cumulative = 0;
-        int ink95 = 10;
-        for (int i = 0; i < 256; i++)
-        {
-            cumulative += inkHist[i];
-            if (cumulative >= target95)
-            {
-                ink95 = Math.Max(i, 5);
-                break;
-            }
-        }
-
-        // 墨迹映射（纯净版，不做任何阴影抑制）
-        for (int i = 0; i < grayData.Length; i++)
-        {
-            int ink = bgData[i] - grayData[i];
-            if (ink < 0) ink = 0;
-
-            double inkNorm = (double)ink / ink95;
-            if (inkNorm > 1.0) inkNorm = 1.0;
-
-            double darkness = Math.Pow(inkNorm, 0.45);
-
-            int val = (int)(255.0 * (1.0 - darkness));
-            if (val < 0) val = 0;
+            int bg = bgData[i];
+            if (bg < 1) bg = 1;
+            int val = (int)((double)grayData[i] / bg * 255.0);
             if (val > 255) val = 255;
             resultData[i] = (byte)val;
         }
 
-        Mat enhanced = new Mat(h, w, MatType.CV_8U);
-        Marshal.Copy(resultData, 0, enhanced.Data, resultData.Length);
+        Mat normU8 = new Mat(h, w, MatType.CV_8U);
+        Marshal.Copy(resultData, 0, normU8.Data, resultData.Length);
 
-        // --- d: USM锐化 ---
+        // --- d: 非线性对比度增强（让文字更黑）---
+        // 除法归一化后文字大约在 180-230 范围（偏亮），需要拉黑
+        // 用 LUT 做分段映射：
+        //   0-180: 线性映射到 0-80（文字区域压暗）
+        //   180-255: 线性映射到 80-255（背景区域保持亮）
+        byte[] lut = new byte[256];
+        for (int i = 0; i < 256; i++)
+        {
+            if (i <= 180)
+            {
+                // 文字区域：压暗
+                lut[i] = (byte)(i * 80 / 180);
+            }
+            else
+            {
+                // 背景区域：拉亮
+                lut[i] = (byte)(80 + (i - 180) * 175 / 75);
+            }
+            if (lut[i] > 255) lut[i] = 255;
+        }
+        Mat lutMat = new Mat(1, 256, MatType.CV_8U, lut);
+        Mat contrasted = new Mat();
+        Cv2.LUT(normU8, lutMat, contrasted);
+        lutMat.Dispose();
+        normU8.Dispose();
+
+        // --- e: USM锐化 ---
         Mat blurred = new Mat();
-        Cv2.GaussianBlur(enhanced, blurred, new OpenCvSharp.Size(0, 0), 1.0);
+        Cv2.GaussianBlur(contrasted, blurred, new OpenCvSharp.Size(0, 0), 1.0);
         Mat sharpened = new Mat();
-        Cv2.AddWeighted(enhanced, 1.8, blurred, -0.8, 0, sharpened);
+        Cv2.AddWeighted(contrasted, 1.8, blurred, -0.8, 0, sharpened);
         blurred.Dispose();
-        enhanced.Dispose();
-
-        // --- e: 对比度加强 ---
-        Cv2.ConvertScaleAbs(sharpened, sharpened, 1.3, -20);
+        contrasted.Dispose();
 
         // --- f: 白底清理 ---
-        Cv2.Threshold(sharpened, sharpened, 220, 255, ThresholdTypes.Trunc);
-        Cv2.ConvertScaleAbs(sharpened, sharpened, 255.0 / 220.0, 0);
+        Cv2.Threshold(sharpened, sharpened, 230, 255, ThresholdTypes.Trunc);
+        Cv2.ConvertScaleAbs(sharpened, sharpened, 255.0 / 230.0, 0);
 
         // 转回3通道
         Mat output = new Mat();