Full text: Technical Commission III (B3)

  
  
  
   
   
  
   
  
    
     
      
   
     
    
    
    
   
    
  
  
    
    
     
   
  
    
    
  
    
   
   
     
   
     
       
   
   
  
   
  
  
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p 
Figure 5. Change trends of brightness, contrast and average gradients when p value from 1-10 in color infrared aerial image shadow 
removal 
6. CONCLUSION 
In this paper, the Shades of Grey (SoG) algorithm based on 
color constancy is explored to remove shadows in true color and 
color infrared urban aerial images. The shadow removal effect is 
analyzed when p (the parameter in Minkowski norm) takes 
different values in each experiment. Three quantitative 
evaluations are utilized to assess quality of the shadow removal 
result. The main results can be described as follows: 
(1)For aerial images, whether true color or infrared, based on 
the shadow detection result, the Shades of Grey algorithm can 
achieve better shadow removal results when p takes a proper 
value. In this paper, this method obtained the best overall 
shadow removal effect as p=2. It is different from the normal 
nature scene images which get good shadow removal result 
when p=6. (2)When p =1, SoG turns into Gray-World one. But 
the result is not as good when p=1. It follows that aerial 
images can not be regarded simply as grey world images, and 
the algorithm based on Gray-World assumptions is not suitable 
for aerial images. 
Since the method used here does not need a priori statistics 
models, and is easier in calculating shadow removal, it is more 
suitable for large area aerial image shadow removal. 
REFERENCE 
Arbel, E. and Hel-Or, H. 2007. Texture-Preserving Shadow 
Removal in Color Images Containing Curved Surfaces. In: 
Proceedings of IEEE Computer Society Conference on 
Computer Vision and Pattern Recognition. Minneapolis, 
Minnesota, U.S.A., pp.1-8 
Buchsbaum, G., 1980. A Spatial Processor Model for Object 
Colour Perception. Journal of Franklin Institute, 310(1), pp. 1- 
26. 
Finlayson, G.D., Hordley, S.D., and Hubel, P., 2001. Color by 
correlation:A simple, unifying framework for color constancy. 
IEEE Transaction Pattern Analysis Machine Intelligence, 23(11) 
pp. 1209-1221. 
Finlayson, G.D., Hordley, S.D., and Drew, M.S., 2002a. 
Removing Shadows from Images. In: Proceedings of the 7th 
European Conference on Computer Vision, Copenhagen, 
Denmark , Part IV, pp. 823-850 
Finlayson, G.D., Hordley, S.D., and Drew, M.S., 2002b. 
Removing Shadows from Images Using Retinex. In: 
Proceedings of IS&T/ SID Tenth Color Imaging Conference: 
Color Science and Engineering Systems, Technologies, and 
Applications, Scottsdale, Arizona, USA, pp.73-79. 
Finlayson, G.D., and Trezzi, E., 2004. Shades of gray and 
colour constancy. In: Proceedings of IS&T/ SID Twelfth Color 
Imaging Conference, Scottsdale, Arizona, USA, pp. 37-41. 
Fredembach, C., et al.., 2005. Hamiltonian Path Based Shadow 
Removal. In: BMVC, Oxford,U.K., Vol. 2, pp. 502-511. 
Land, E. and McCann, J., 1971. Lightness and Retinex Theory. 
Journal of the Optical Society of America, 61(1),pp. 1-11 
Shor, Y. and Lischinski, D., 2008 The Shadow Meets the Mask: 
Pyramid-Based Shadow Removal. Computer Graphics Forum, 
27(2), pp. 577-586 
Susuki, A., Shio, A., Arai, H., and Ohtsuka, S., 2000. Dynamic 
shadow compensation of aerial images based on color and 
spatial analysis. In: Proceedings of the 15th International 
Conference on Patten Recognition, Barcelona, Catalonia, Spain, 
Vol. I , pp.317-320. 
Weijer, J. van de, Gevers, Th., Gijsenij, A., 2007. Edge-Based 
Color Constancy. IEEE Transaction Image Processing, 16(9), 
pp. 2207-2214. 
Joint ISO/CIE Standard ISO 11664-2:2007(EYCIE S 014- 
2/E:2006 
http://www.cie.co.at/index.php/index.php?i ca_id=484 
ACKNOWLEDGEMENTS 
The aerial images dates was supported by Shanghai Municipal 
Institute of Surveying and Mapping in this research. The author 
would like to thank for the help. 
KEY WC 
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