opencvsharp踩坑DAY2--图像增强illuminate

标签：illuminate Mat -- dealing object int 灰度 images 图像增强

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<byte>(x, y)、Mat.Get<int>(x, y)、Mat.Get<uint>(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         }

 

 

 

   

标签：illuminate,Mat,--,dealing,object,int,灰度,images,图像增强
From： https://www.cnblogs.com/shtnm/p/16635288.html