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Of five levels 
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et of orien- 
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ccn 
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date of flight t 
i iine Frequency: 92.978 Hz 
altitudes 
  
Figure 1. 
4. Example: MEOSS airborne data strip Dorfen 
4.1 Image material and image matching details 
The data strip Dorfen can be seen in Figure 1. The 
images of the foreward, nadir and backward looking 
sensors are shown in parallel strips of simultaneously 
acquired image lines. The along-track displacement 
between the images of the same objects (one base 
length) corresponds to about 2400 image lines. The 
platform, sensor and image parameters are displayed 
in Table 1. 
The numbers of points extracted by the interest opera- 
tor and being left after the digital image correlation are 
given in Table 2 for the five levels of the resolution 
pyramid. 
For the manual start at lowest level of resolution 52 and 
33 conjugate points were extracted from the back- 
ward/nadir and forward/nadir stereo pairs, respective- 
ly. The difference in the numbers can be explained by 
the different information content of the stereo pairs. 
Data of MEOSS Satellite Model Flown on Board of Aircraft D-CHET of 
DLR x 
  
  
. 
P Bua X E s 
inadir Looking! LCD $ (backward Looking! 
number of CCD elements: 
size of CCD elements 
71 
relatiue radiometric decalibration 
3236 stereo look angle: 23.52 deg 
18,7 Hm 2m by 2m image processing? DLR-DIBIAS / Le 
ground resolution! 2 
MEOSS Dorfen strip 
  
Platform Parameters 
ground speed 
altitude 
660 km/h 
11335 m 
Sensor Parameters 
objective 
focal length 
stereo angle 23.52 degrees 
CCD element size 10.7 micrometer 
number of elements per array 3236 
Zeiss Biogon 
61.1 mm 
line frequency 92.978 Hz 
Image Parameters 
ground resolution in flight direction 2m 
ground resolution cross flight 2m 
length of strip 8416 lines / 16.6 km 
swath width 3236 pixels / 6.4 km 
  
  
swath width for triple stereoscopy 3000 pixels / 6.0 km 
  
Table 1. Platform, sensor and image parameters for 
MEOSS Dorfen strip 
The computer time requirement for image matching is 
about 1/2 day per baselength on modern RISC-type 
workstations. It could be further reduced by streamlin- 
ing of the software and - more drastically - by using 
parallel computing. Both, interest operator and image 
correlation tasks, can easily be distributed in terms of 
different image regions to any number of CPUs.