Full text: Actes du Symposium International de la Commission VII de la Société Internationale de Photogrammétrie et Télédétection (Volume 1)

rite Xu e e Load 
  
In order.to reduce the signal film histories to a digital image, this facility 
consists of a coherent optical processor interfaced:to an image dissector under 
computer control. The data at the output plane were digitized with an image 
dissector using 256 gray levels and the resulting samples were recorded on 
computer compatible tape (CCT). A sample spacing of. 0.75 m was used in both 
slant range and azimuth (1.5 m resolution in slant range sampled twice in 
accordance with the Nyquist theorem). Investigations done at ERIM (Ref.2) 
showed that the slant range and azimuth impulse point response (IPR) achieved 
during these flights of the SAR 580 system was not quite as good as the nominal 
values of 1.5 m for range and 2.1 m for azimuth. The measured IPR (3 db width) 
was 2.3 m in slant range and 2.2 m in azimuth for X-Band (3.2 cm) and 3.3 m 
in slant range and 3.9 m in azimuth for L-Band (23.5 cm). A one-dimensional 
convolution resampling operation was used to transform these data from slant 
range to ground range coordinates. In order to be able to overlay the data of 
different wavelengths and flight passes, which were chosen perpendicular to 
each other by the SWISSAR Investigation Team, I resampled to a 1.5 mby 1.5m 
grid system on the ground. The L-Band imagery was found to be of lesser quality 
than X-Band imagery. In view of this and the resources required to carry out the 
digitization, I chose to concentrate my current study to the seven data sets 
depicted in Figure 2 instead of all twelve which were available. 
  
Figure 
Data S 
  
à An affine transformation with coefficients 
Palio: determined by a least squares fit was 
nau used to transform SAR slant to ground 
Test Area range corrected imagery from each data 
M set (flight direction/-wavelength/po- 
larization) to a coordinate system based 
upon a 1:25'000 scale topographic map. In 
order to determine the best linear trans- 
SE formation between the map coordinate 
714 XHV (M > M.) and radar image coordinate 
A (Ri; Rp)» I estimated the six coefficients 
da using a set of 10 common points on both ; 
the map and each of the seven data sets. Figure 
These points (typically field corners) Data: Sc 
were chosen well distributed throughout 
the entire test area. Their locations 
were determined visually using 
1024 x 1024 images. For flight pass 709 
Ou) the least squares fit based upon 
the control points resulted in the 
following coordinate transformation 
Eqs; "T and 2. 
  
  
  
  
  
hs 
711 XHH «4 
  
  
  
Figure 2. Flight Direction and 
Wavelength/Polarization Selection 
R 
|7 7.15221 M, - .44533 M, + 760.05 (1) 
Ry 
-.24885 M, + -07889 M, + 285,71 (2) 
Applications of this kind of transformation to the control points themselves 
provide an estimate of the accuracy of the least Squares fit. The regression 
coefficient, r2, was 0.99976 for predictions in scan line direction and 0.99940 
for predictions in pixel direction. The mean Square error was 8.13 in the scan Figure 
line direction and 6.14 in the pixel direction, which corresponds to a mean Data Se 
error of lessthan 4 pixels (6 meters). This procedure was repeated for each 
  
232 
uM MEE [5 8 5 5 1 0 I ROS SSR 7 
a OO” 
 
	        
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