出差摸鱼做的一个用opencvsharp的东西,用于快速验证,水平极差,目前功能如下

今天搞的功能是复现halcon的图像增强算子illuminate,根据文档其运作过程为
1.输入均值(低通)滤波矩阵size,输入Factor,原图灰度集in
2.滤波in得图像m
3.然后out= round ( (val - m) * Factor + in )
4.其中val在halcon帮助中描述为For byte-images val equals 127, for int2-images and uint2-images val equals the median value. 而这个byte-images、int2-images、uint2-images区分则是其图像类型,参考大佬http://www.skcircle.com/?id=1547,在opencvsharp中则分别对应了遍历图像Mat.Get(x, y)、Mat.Get(x, y)、Mat.Get(x, y)的值,而127也是0-255的中只所以选择该数值作为val。在本文中用到的图像类型默认是byte-images。
5.其中Factor与滤波器尺寸成正相关关系halcon说明中30x30到200x200的范围有以下几种组合
Height Width Factor
---------------------
40 40 0.55
100 100 0.7
150 150 0.8
6.综合上文,得知在低通滤波后图像将灰度中值比较,将其间差乘以因子Factor再加上原灰度值。让局部的灰度向灰度中值靠拢以达到增强图像的高频区域(边缘和拐角),使图像看起来更清晰的效果。原文:Very dark parts of the image are “illuminated” more strongly, very light ones are “darkened”.
halcon效果如图

opencvsharp实现效果如下- 1 private void illuminate()
- 2 {
- 3 int w, h;
- 4 double factor;
- 5 Cv2.CvtColor(dealing_object, dealing_object, ColorConversionCodes.BGR2GRAY);
- 6 Mat mean = new Mat();
- 7 w = int.Parse(InputBox("滤波器宽", "", ""));
- 8 h = int.Parse(InputBox("滤波器高", "", ""));
- 9 factor = double.Parse(InputBox("系数", "", ""));
- 10 Cv2.Blur(dealing_object, mean, new OpenCvSharp.Size(w, h));
- 11
- 12 Mat output = new Mat(dealing_object.Size(), dealing_object.Type());
- 13 for (int i = 0; i < dealing_object.Height; i++)
- 14 {
- 15 for (int j = 0; j < dealing_object.Width; j++)
- 16 {
- 17 int v = (int)Math.Round((172- mean.Get<byte>(i, j)) * factor) + dealing_object.Get<byte>(i, j);
- 18 v = v > 255 ? 255 : v;
- 19 v = v < 0 ? 0 : v;
- 20 output.Set(i, j, v);
- 21
- 22 }
- 23 }
- 24 Cv2.ImShow("in", dealing_object);
- 25 Cv2.ImShow("out", output);
- 26
- 27 }
复制代码

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