图像聚焦算法--清晰度评价函数

Halcom

图像聚焦算法--清晰度评价函数

1. *使用halcon自带的图片
   
2. *实现了五种评价函数，
   
3. *选择算子的Method值，可以观察不同评价函数的效果。
   
4. read_image (Image, 'pcb_focus/pcb_focus_telecentric_106')
   
5. dev_update_off ()
   
6. dev_close_window ()
   
7. dev_open_window_fit_image (Image, 0, 0, 752, 480, WindowHandle)
   
8. set_display_font (WindowHandle, 16, 'mono', 'true', 'false')
   
9. dev_set_color ('lime green')
   
10. dev_set_line_width (3)
    
11. Ret:=[]
    
12. get_image_size(Image, Width, Height)
    
13. for Index := 1 to 121 by 1
    
14.     read_image (Image, 'pcb_focus/pcb_focus_telecentric_'+Index
    
15. 
    
16.     evaluate_definition (Image, 'Tenegrad', Value)
    
17.    
    
18.     dev_display (Image)
    
19.     Ret:=[Ret,Value]
    
20. endfor
    
21. *使用直方图显示清晰度结果，如果有更好的方法，那就跟帖回复吧
    
22. VMax:=max(Ret)
    
23. VMin:=min(Ret)
    
24. GRet := 100*(Ret-VMin)/(VMax-VMin)
    
25. gen_region_histo(Region, Ret, 255, 255, 1)
    
26. *找到峰值对应的那张图，确实是最清晰的那张。
    
27. qxd:=find(Ret, max(Ret))
    
28. read_image (GoodImage, 'pcb_focus/pcb_focus_telecentric_'+qxd
    
29. 
    
30. dev_display (GoodImage)
    
31. dev_display (Region)
    
32. evaluate_definition函数代码如下：
    
33. 
    
34. scale_image_max(Image, Image)
    
35. get_image_size(Image, Width, Height)
    
36. 
    
37. if(Method = 'Deviation')
    
38. *方差法
    
39.     region_to_mean (Image, Image, ImageMean)
    
40.     convert_image_type (ImageMean, ImageMean, 'real')
    
41.     convert_image_type (Image, Image, 'real')
    
42.     sub_image(Image, ImageMean, ImageSub, 1, 0)
    
43.     mult_image(ImageSub, ImageSub, ImageResult, 1, 0)
    
44.     intensity(ImageResult, ImageResult, Value, Deviation)
    
45.    
    
46. elseif(Method = 'laplace')
    
47. *拉普拉斯能量函数
    
48.     laplace (Image, ImageLaplace4, 'signed', 3, 'n_4')
    
49.     laplace (Image, ImageLaplace8, 'signed', 3, 'n_8')
    
50.     add_image(ImageLaplace4,ImageLaplace4,ImageResult1, 1, 0)
    
51.     add_image(ImageLaplace4,ImageResult1,ImageResult1, 1, 0)
    
52.     add_image(ImageLaplace8,ImageResult1,ImageResult1, 1, 0)
    
53.     mult_image(ImageResult1, ImageResult1, ImageResult, 1, 0)
    
54.     intensity(ImageResult, ImageResult, Value, Deviation)
    
55. 
    
56. elseif(Method = 'energy')
    
57. *能量梯度函数
    
58.     crop_part(Image, ImagePart00, 0, 0, Width-1, Height-1)
    
59.     crop_part(Image, ImagePart01, 0, 1, Width-1, Height-1)
    
60.     crop_part(Image, ImagePart10, 1, 0, Width-1, Height-1)
    
61.     convert_image_type (ImagePart00, ImagePart00, 'real')
    
62.     convert_image_type (ImagePart10, ImagePart10, 'real')
    
63.     convert_image_type (ImagePart01, ImagePart01, 'real')
    
64.     sub_image(ImagePart10, ImagePart00, ImageSub1, 1, 0)
    
65.     mult_image(ImageSub1, ImageSub1, ImageResult1, 1, 0)
    
66.     sub_image(ImagePart01, ImagePart00, ImageSub2, 1, 0)
    
67.     mult_image(ImageSub2, ImageSub2, ImageResult2, 1, 0)
    
68.     add_image(ImageResult1, ImageResult2, ImageResult, 1, 0)   
    
69.     intensity(ImageResult, ImageResult, Value, Deviation)
    
70. elseif(Method = 'Brenner')
    
71. *Brenner函数法
    
72.     crop_part(Image, ImagePart00, 0, 0, Width, Height-2)
    
73.     convert_image_type (ImagePart00, ImagePart00, 'real')
    
74.     crop_part(Image, ImagePart20, 2, 0, Width, Height-2)
    
75.     convert_image_type (ImagePart20, ImagePart20, 'real')
    
76.     sub_image(ImagePart20, ImagePart00, ImageSub, 1, 0)
    
77.     mult_image(ImageSub, ImageSub, ImageResult, 1, 0)
    
78.     intensity(ImageResult, ImageResult, Value, Deviation)
    
79. elseif(Method = 'Tenegrad')
    
80. *Tenegrad函数法
    
81.     sobel_amp (Image, EdgeAmplitude, 'sum_sqrt', 3)
    
82.     min_max_gray(EdgeAmplitude, EdgeAmplitude, 0, Min, Max, Range)
    
83.     threshold(EdgeAmplitude, Region1, 11.8, 255)
    
84.     region_to_bin(Region1, BinImage, 1, 0, Width, Height)
    
85.     mult_image(EdgeAmplitude, BinImage, ImageResult4, 1, 0)
    
86.     mult_image(ImageResult4, ImageResult4, ImageResult, 1, 0)
    
87.     intensity(ImageResult, ImageResult, Value, Deviation)
    
88.    
    
89. elseif(Method = '2')
    
90. 
    
91. elseif(Method = '3')
    
92.    
    
93. endif
    
94.    
    
95. return ()

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参考：https://blog.csdn.net/wuan584974722/article/details/51435876