latle 7. influence of Model's beformation 
  
  
  
  
  
  
  
C s odel Ch ck Foi nts | on ce RMS Z ————————-—— 
tese | e No Correction | Correction Done 
| 10 1.87 m 0.89 m 
ere ee ee NT TT 
[450 11 1.62 m 0.84 m 
| 
- BX ra ERR TR OAL 
: 4 12 2.14 m 0.84 m 
  
  
  
  
  
2.2 Resampliing along the epipolar lines 
bpipolar line is a well known conception to photogrammetrists. 
Using this concept a inherent two- dimensional correlation task can 
be reduced to one-dimensional matching problem. It is extremely 
important to rearrange image data along epipolar lines, because 
only under this circumstance it becomes possible to process a large 
amount of image data by tne use of a small capability of memory. 
In accordance with traditional way resampling along epipolar lines 
is treated as a digital rectification problem, in which four pixels 
have to be involved for extracting one resampled pixel (Fig 3.a). 
lt is time-consuming for bilinear interpolation. 
Epipolar line 
277 
T. 
  
  
  
  
  
NIS 
p 
(a) 
  
  
  
  
  
  
  
  
  
  
  
  
Fig. 5. Resampling along epipolar lines 
In the SODAMS a new approach has been available, in which only two 
neighbordhood pixels are needed to derive one pixel on epipolar 
line (Fig.5.b). In fact a further step can be taken to simplify the 
resampling procedure with tne help of the nearest neighborhood 
method instead of linear interpolation (Fig.3.c). With this approxi- 
mate measure there is no effect on further processing -- correlation. 
Therefor, the resampling along epipolar lines can be simplified as 
a procedure to pick up corresponding groups of pixels from origi- 
nally digitized images (Fig.3.c). It is powerful and timesaving to 
run the program written in such way mentioned above. 
2.3 Digital correlation 
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