The International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences. Vol. XXXVII. Part Bl. Beijing 2008 
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A final report on the DLR/IMF results achieved for CSAP 
together with a set of DSM and orthoimages has been delivered 
to ISRO/SAC. A copy of the report can be provided to 
interested readers. 
1.2 DLR test sites for CSAP 
DLR/IMF takes part in CARTOSAT-1 Scientific Assessment 
Program (C-SAP) as a principal investigator for German 
(Southeast Bavaria) and Spanish (Catalonia, test site 10) test 
sites, and as a Co-I in the evaluation of CARTOSAT-1 data for 
test site 5 (Mausanne-les-Alpilles, France). In all cases rational 
polynomial functions (RPC) are provided by the distributing 
Indian agency ISRO/SAC as a universal sensor model for each 
scene. Table 1 shows the imaging dates and the centre roll angle 
which is varying substantially (e.g. for Mausanne scenes for 
producing the overlap). 
Abbreviation for 
the paper for aft 
and fore scenes 
Imaging date 
Centre-roll (deg) 
(for aft image) 
Mausanne-les-Alpilles (France), test site 
5 
MAI /MF1 
31Jan2006 
-13.6 
MA2 / MF2 
06Feb2006 
4.0 
Catalonia (Spain), test site 10 
Cat-A / Cat-F 
01Feb2006 
-0.1 
Bavaria (Germany) 
Bav-A / Bav-F 
30Apr2007 
9.5 
Table 1 : The 4 stereo pairs used for C-SAP at DLR 
Some numbers in the tables given in this paper may be slightly 
different from those in (Lehner et al. 2006/2007) because the 
original RPC delivered with the images had zero denominator 
problems and were later replaced with new RPC by ISRO/SAC. 
2. DLR STEREO PROCESSING 
2.1 Image matching 
Hierarchical intensity based matching as implemented into the 
XDibias image processing system of DLR/IMF consists of two 
major steps (Lehner and Gill 1992; Komus et al. 2000). In a 
first step the matching process uses a resolution pyramid to 
cope even with large stereo image distortions stemming from 
carrier movement and terrain. Large local parallaxes can be 
handled without knowledge of exterior orientation (which is 
often not available with sufficient accuracy for space-borne 
imagery). The selection of pattern windows is based on the 
Foerstner interest operator which is applied to one of the stereo 
partners (chosen according to the best radiometric properties - 
in case of CARTOSAT-1 this is the aft image). For selection of 
search areas in the other stereo partner(s) local affine 
transformations are estimated based on already available tie 
points in the neighborhood (normally from a coarser level of the 
image pyramid; on the coarsest level (factor 64 reduction in 
case of CARTOSAT-1 stereo pairs) the parallaxes and shifts are 
already so small that the process can be started automatically 
just using adapted (larger) window sizes for patterns and search 
areas). Tie points with an accuracy of one pixel are located via 
the maximum of the normalized correlation coefficients 
computed by sliding the pattern area all over the search area. 
These approximate tie point coordinates are refined to sub-pixel 
accuracy by local least squares matching (LSM). The number of 
points found and their final (sub-pixel) accuracy achieved 
depend mainly on image similarity and decrease with increasing 
stereo angles or time gaps between imaging. The software was 
originally devised for along-track 3-line stereo imaging (stereo 
scanners MEOSS and MOMS operated by DLR). Normally, the 
procedure can be executed fully automatically if the shift 
between the stereo partners is small compared to the image size 
as is true for CARTOSAT-1 stereo pairs. The procedure results 
in a rather sparse set of tie points well suited for introducing 
them into bundle adjustment and as an excellent source of seed 
points for further densification via region growing (second step). 
The second step uses the region growing concept first published 
by Otto and Chau in the implementation of TU Munich (Heipke 
et al. 1996). It combines LSM with a strategy for local 
propagation of initial conditions of LSM. 
Various methods for blunder reduction are used for both steps 
of the matching: 
• Threshold for correlation coefficient 
• Bi-directional matching and threshold on resulting 
shifts of the coordinates 
• Quasi-epipolar reprojection of tie point coordinates 
In areas of low contrast the propagation of affine transformation 
parameters for LSM in the region growing process leads to high 
rates of blunders. In order to avoid intrusion into homogeneous 
image areas (e.g. roof planes and agricultural fields without 
structure) the extracted image chips are subject to (low) 
thresholds on variance and roundness of the Foerstner interest 
operator. This and the many occlusions found in densely built- 
up areas imaged with a large stereo angle create lots of 
insurmountable barriers for region growing. Thus, for high 
resolution stereo imagery the massive number of seed points 
provided by the matching in step one (image pyramid) turns out 
to be essential for the success of the region growing. 
The numbers of tie points found and their sub-pixel accuracy is 
highly dependent on the stereo angle. A large stereo angle 
(large base to height ratio b/h) leads to poorer numbers of tie 
points and to lower accuracy in LSM via increasing 
dissimilarity of the (correctly) extracted image chips. 
For currently available high resolution stereo imagery the stereo 
angle is too large, at least for built-up areas. The importance of 
a large base-to-height ratio is exaggerated at the cost of the 
matching accuracy and density (see Krauss et al. 2006). The 
accuracy in forward intersection is inversely proportional to the 
base-to-height ratio but also direct proportional to the matching 
accuracy (parallax measurement). The latter and the matching 
density are improved by reducing the stereo angle. In table 2 
past and current stereo missions are shown together with their 
stereo angles. In contrast to the drastic reduction in ground 
sampling distance (GSD) the stereo angles are growing instead 
of decreasing. Thus, image matching performance is much 
hindered because of the appearance of more and more complex 
natural and man-made objects in the images. For IKONOS-2 
the possibility for smaller stereo angles exits. As indicated in 
the table 2 DLR managed to get examples with 10 and 6 degree 
stereo angles and the advantage for image matching could be 
shown (Krauss et al. 2006). An increase in the accuracy of the 
parallax measurement via finer resolution allows for a decrease 
of the stereo angle to improve matching performance.