I. 
; 
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Figure 13. The boundaries of Building2: Light Blue one was 
generated by the real 1 meter Lidar data; Green one was 
generated by the 3 meter Lidar data; and Red one was 
generated by the densified 1 meter Lidar points. The bar in 
the middle of the drawing represents 10 meter distance. 
  
  
  
Figure 14. The boundaries of Building3: Light Blue one was 
generated by the real 1 meter Lidar data; Green one was 
generated by the 3 meter Lidar data; and Red one was 
generated by the densified 1 meter Lidar points. The bar in 
the middle of the drawing represents 10 meter distance. 
4. THE FEASIBILITY OF THE APPROACH, 
ITS POTENTIAL APPLICATIONS, AND FUTURE 
WORKS 
The experimental results shown in the Section 3 demonstrate 
that the approach and the LPDS developed based on it are 
effective and efficient in using stereo images to generate 3D 
points with the help of an existing Lidar data. The generated 
3D points are complement to the existing Lidar data and 
when the generated 3D points are added to the existing Lidar 
data, the existing Lidar data is densified to meet the needed 
data point spacing. The experimental results also show that 
the densified Lidar data points have high quality in terms of 
preserving building shapes and keeping the accuracy. 
The high quality of the densified Lidar data allows it to be 
used.in any applications where high quality Lidar data is 
needed. One particular application of using the densified 
Lidar data is for making True Orthophotos. It is well known 
that the quality requirement on the DEMs for making True 
Orthophotos is very high. Such DEMs have to have accurate 
building shapes, building elevations, and high point density. 
It is very expensive to collect such DEMs manually and 
extremely difficult, if not impossible, to generate them 
automatically from frame imagery. The availability of the 
densified Lidar data would provide the needed high quality 
and also reduce the cost of data acquisition. 
While this paper is being prepared, more tests are going to be 
conducted. The goal for the further tests is to fine turn the 
International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences, Vol XXXV, Part B3. Istanbul 2004 
image matching parameters and make the LPDS a production 
level system. 
S. REFERENCES 
Grün at al. (eds), 1995. Automatic Extraction of Man- 
Made Objects from Aerial and Space Images. 
Birkhauser-Verlag, Basel, 
Moffitt, F. and Mikhail, E., 1980. Photogrammetry. Third 
Edition. Harper & Row, N.Y., NY. Pp443-444. 
Wang, Z., and Schenk, A., 2000. Building Extraction and 
Reconstruction from Lidar Data. The Proceedings of 19th 
ISPRS Congress, Amsterdam, The Netherlands. CD. 
     
  
  
  
   
   
  
  
   
  
   
   
   
  
   
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
   
   
   
  
  
   
   
  
  
  
  
   
  
  
   
   
  
  
   
  
  
  
  
  
   
     
   
  
  
  
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