Full text: XVIIIth Congress (Part B3)

       
    
  
  
   
     
   
   
   
   
    
     
     
    
    
  
  
  
   
    
  
   
    
  
   
   
   
   
    
   
   
    
    
    
    
   
  
       
   
    
    
    
   
    
  
    
    
   
   
  
    
    
    
   
AERIAL 
Reconstruction, 
rge scale aerial 
ficulties for the 
topographical 
thed contours. 
ted as supplied 
ng illumination 
atment as well 
face is a Lam- 
)ntinuous 2i-D 
.. Keeping this: 
reconstruction 
] mathematical 
tection and for 
nts of postpro- 
istinguish three 
cannot exactly 
rich only occur 
7. image blun- 
1g the exposure 
1. We prove by 
more than two 
ble. 
noise: Surface 
tion of surface 
ess can not be 
s the bound to 
cannot be cir- 
plied by Facets 
detection and 
ency of the 25- 
ust be approxi- 
should remedy 
it Facets Stereo 
eliminate parts 
of the surface — of course the outer surfaces of buildings, 
leaved trees, parking cars, etc. become part of the recon- 
structed surface. 
The examples presented in this paper deal with these prob- 
lems and show the surface reconstruction results of appropri- 
ate areas. 
3 SCENE AND DATA 
We use 4 black and white aerial images for our experiments, 
cf. fig. 1. They are taken by the aerial camera ZEISS RMKA 
with an image format of 23 x 23cm? and a calibrated focal 
length cx = 153mm. The flying altitude of 600m above 
ground corresponds to an image scale mp ~ 1 : 4000. The 
exposures were taken in the south of Germany at the be- 
ginning of springtime, so the vegation is still leafless. The 
exposure interval between the images 133/135 and 268/270 
is about 20min. 
  
Figure 1: Overlap of aerial images (mp ~ 1 : 4000) in rela- 
tion to the reconstructed orthophoto 
The images were scanned by the photogrammetric scanner 
ZEISS PS1, with 8bits per pixel and a pixelsize of 15x 15um?. 
The mathematical model of Facets Stereo Vision deals with 
noisy image data — straightforward, neither geometric nor 
radiometric preprocessing of the images has been applied. 
The scene contains different degrees of difficulty of topo- 
graphical surface types: Relatively flat agricultural areas, 
steep slopes, different kinds of leaved and unleaved vegetation 
and man-made objects like buildings and highway bridges. 
In our experience, difficulties of surface reconstruction usually 
grow within the multigrid process by growing image scale. So 
we choose an image scale as large as possible to get in contact 
with all of the problems of terrain noise and discontinuities 
in object space. As distortions like image blunders usually 
disappear at higher levels of the image pyramid, the perfor- 
mance of Facets Stereo Vision concerning this point, too, can 
be shown to be best at finest image resolution. Consequently, 
in this paper we only present results gained with the original 
pixel values and resolution from scanning. 
4 PARAMETER SETTINGS AND SOME SPECIAL 
HINTS 
We started the multigrid process at the 9th level of the image 
pyramid. The corresponding resolutions are given in tab. 1. 
759 
International Archives of Photogrammetry and Remote Sensing. Vol. XXXI, Part B3. Vienna 1996 
Start values for the heights were obtained by simply bilinear 
interpolating the coordinates of four outlying tiepoints from 
the bundle block adjustment. 
  
  
level: | pixel /facet: size: 
image pixel 4 x 4mm? in image space 
orthoimage facet 32 x 32m? in object space 
9 ~ 2 X 2 image pixels 
height facet 128 x 128m? in object space 
~ 8 x 8 image pixels 
image pixel 15 x 15um^ in image space 
orthoimage facet 12.5 x 12.5cm? in object space 
1 ~ 2 X 2 image pixels 
height facet 50.0 x 50.0cm? in object space 
~ 8 x 8 image pixels 
  
Table 1: Facet parameters and image pixel sizes for highest 
and lowest multigrid level 
The test area covered ~ 600 x 600m? in object space, cor- 
responding to ~ 1.4 - 10° estimated height parameters and 
~ 22.4-10° estimated orthoimage grey value parameters. Be- 
cause of the high image noise of go ~ 46 — 8 grey values we 
choose non adaptive curvature minimization as regularization 
procedure with a weight factor of À = 1 - 10°. The relativly 
large size of the heigt facets in relation to the pixel size causes 
some implicit regularization, too. 
In principle, the long time delay (cf. section 3) between the 
two flight strips can be taken into account by simultaneously 
estimating one separate set of orthoimage parameters for the 
images of each strip. The basic idea of this proceeding is very 
similar to the treatment of color images, as explained by [1]. 
By that way, the different surface texture caused by different 
shadow locations in the images of the different strips can be 
taken into account precisely. In this paper we treat all images 
as isochronous exposures. So, small errors in those regions, 
were shadow gives texture, have to be expected. 
The contours plotted into the orthoimages on the following 
pages of this paper exactly reproduce the results obtained by 
Facets Stereo Vision by bilinearly interpolating within each 
height facet for every orthopixel position. Please note, that 
our goal for this paper is to document the original reconstruc- 
tion results of Facets Stereo Vision, but not the results of any 
additional fine contour smoothing algorithm! 
We believe that it might be useful not only to offer height and 
orthoimage data, but also the accompanying quality criteria 
to a further semantic analysis. This in mind, the decision 
whether to build a 'good looking' smooth result or not should 
be dependent on the aim of the following data procession 
steps. 
5 ACCURACY CHECKS 
We obtained the parameters of the outer orientation of im- 
ages by bundle block adjustment based on image coordinates 
measured in the analogue images. The bundle block ad- 
justment reached an accuracy of +3cm for the height com- 
ponent of the tiepoints in object space. To ensure that 
the set of our transformation parameters is really correct 
for the digital images, we compared a set of 10 signalised 
control points with the corresponding interpolated heights 
of Facets Stereo Visions surface reconstruction: The abso- 
lute height differences all were less than |AZmaz| < 10cm,
	        
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