Full text: Proceedings, XXth congress (Part 3)

  
International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences, Vol XXXV, Part B3. Istanbul 2004 
  
calculated by the LBTM are almost identical to those obtained 
from the ordinary 3D/2D affine models and GCPs. Applying 
different configurations of the control straight lines indicates 
that the inclination angle (the angle in the XY plane) of the 
control line does not affect significantly the accuracy of the 
results but the distribution of the GCLs on the area covered by 
the image does. Increasing the number of GCLs improves the 
accuracy of the results; however, a key feature established from 
these results is that the GCL slope, which is a function of the 
GCL length and terrain elevation differences along the line, has 
the most important effect on the results accuracy. The results 
presented below are chosen to illustrate this phenomenon. 
  
600 
500 
400 
-300 
-400 
— GC ES 
  
-Sv0 Checkpoints 
  
  
  
-600 i 
-600 -S00 -400 -300 -200 -100 0 100 200 300 400 500 600 
Figure 2. GCLs and checkpoints distribution of Sland S2 sets 
  
600 — 
500 
400 i 
m x 
300 S 
y 
0 p nin i ; 
-100 NC 4 
9 3 
-200 
-300 : / Ji 
-400 
N —— GCLs 
-S00 Checkpoints 
-600 
-600 -506 -400 -300 -200 -100 0 100 200 300 400 5060 600 
  
  
  
Figure 3. GCLs and checkpoints distribution of S3 and S4 sets 
  
  
  
  
  
  
  
  
  
  
Data Set  |No. of| No. of The 3D affine LBTM 
GCLs |Chkpts Total RMS (m) 
x Y 
= [Case Si | 4-12 | 24 | 532-292 | 204-226 
B | Case S2 0.20-0.21 | 0.29- 0.23 
£ |Case S3 4.32-3.27 | 4.21-2.62 
A | Case S4 203-147 | 1.84- 1.67 
Real (HK) | 4-12 | 16 | 9.01-2.39 | 6.96-2.01 
  
  
  
real data 
Table 1: The 3D affine LBTM results of the synthetic and the 
  
  
  
  
  
  
  
  
  
  
Data Set No. of| No. of The 2D affine LBTM 
GCLs |Chkpts Total RMS (m) 
X Y 
9 [CaseS1| 4-12 | 24 | 3.81-3.01 | 6.99-4.60 
2 | Case S2 0.46-0.28 | 1.10-0.51 
E | Case S3 3.96-2.17 | 5.77-6.31 
N | Case S4 3.76- 1.49 1.63- 0.46 
Real (HK) | 4-12 | 16 | 7.73-5.09 | 8.19-9.14 
  
  
  
real data 
Table 2: The 2D affine LBTM results of the synthetic and the 
854 
When considering the effect of the terrain type, the results in 
Table 1 indicate that data set S2 (flat terrain) yields more 
accurate results than data set SI (undulated terrain) in all 
directions, the same way as data set S4 leads to more accurate 
results than data set S3. The results also show that the sharper 
the slopes of GCLs are, less accurate the results are. Applying 
the 2D affine LBTM to the same data sets leads to similar 
findings; however, the overall accuracy is generally worse than 
when using the 3D affine LBTM. The deficit of the results is 
especially clear when applying the 2D affine LBTM to the sets 
of the undulated terrain. This finding is expected because the 
2D LBTM does not consider the differences in terrain clevation. 
On the basis of the above, one can conclude that the selection of 
the LBTM form to be used for image rectification depends 
primarily on terrain elevation differences. In the following 
section a real data set is used to examine the feasibility and the 
performance of the developed model. 
3.2 Real Data 
To verify the results obtained from the simulated data, a real 
stereo data set (Ikonos Hong Kong data set) was used. The area 
covered by the two images extends over 11.60 x 10.28 km? for 
image 1 and 6.62 x 10.18 km? for image 2 of the stereo with the 
overlap area of 2.5 x 10 km?. The inclination angles of the 
images are 19.02 and 27.3 degrees respectively, which leads to 
the base to height (B/H) ratio of about 0.87. The maximum 
ground elevation difference in the test area is about 450 meters. 
A fast static GPS technique was used to collect thirty-eight 
well-distributed GCPs on the entire coverage area of the two 
images; among them, eighteen GCPs belong to the overlap area. 
Most of the observed points were road intersections, pavement 
corners, or road-canal intersections. Further information about 
the test field can be found in Shi and Shaker, 2003 and Shaker 
et al., 2004. 
A number of GCLs were established by connecting different 
points in the overlap area between the two images and the 3D 
LBTM was applied. The results show that the new model is 
applicable to the real data, though solid conclusions could not 
be drawn as the data set had limited overlap coverage area 
(2.5x10 km?) and dependent checkpoints (the same 18 points 
which are used to establish the GCLs). Consequently, the 
coverage area of image 2 of the data set (6.62 x 10.18 km?) was 
extended to cover the same area as in image 1 (11.60 x 10.28 
km?). The image coordinates of the extension area of image 2 
were calculated by using the ground coordinates of the 
observed GPS points, the corresponding image coordinates of 
image 1, and the ordinary affine model parameters as they 
defined in Shi and Shaker, 2003. Accordingly, the two image 
coordinates and the object coordinates of, a set of the 38 points 
were ready for the experiment. 
After several attempts to generate control straight lines, a group 
of 12 GCLs were established by connecting some of the GCPs 
of the data set keeping in mind that the lines were matching real 
linear features such as roads or canals. The remaining points 
were used as checkpoints (16 independent checkpoints). The 
final distribution of GCLs and checkpoints used in this 
investigation are presented in Figure 4. 
The accuracy of the results of applying the established GCLs 
plus one additional GCP to the developed LBTM was found to 
be matching the accuracies which resulted from using the 
simulated data. It is important to mention that the data set did 
not contain any high slope GCL; however, the GCLs 
comprising in the data set presented different levels. Tables ! 
IT
	        
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