XIX-B3, 2012 
'ocess is depicted in 
-artosat-2 multiview 
titude and position 
ta files. Using the 
ition parameters are 
ents are computed in 
nages are generated 
sed for generating 
odel. The edges of 
ion and refinement 
matched in another 
e manually digitized 
t is computed for the 
t is subtracted to get 
buildings and digital 
ng and visualization 
on of | 
SM 
ITEM 
ind 
  
  
1eration system. 
SSION 
ntation of multiview 
> identified on the 
| for computation of 
ults are shown on 
he image position in 
' conjugate point is 
mated positions are 
: difference between 
International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences, Volume XXXIX-B3, 2012 
XXII ISPRS Congress, 25 August — 01 September 2012, Melbourne, Australia 
the actual and estimated position is shown in line and pixel 
direction. The achieved average value is 0.02 and -0.001 pixels 
in line and pixel directions respectively. The standard deviation 
is 1.392 and 0.99 in line and pixel direction respectively. 
Table 1 Results of Relative orientation of Multi-view images of 
Cartosat-2 images (Washington) 
  
  
  
  
  
  
  
  
  
  
  
  
  
  
[Actual Actual Estimated Residual error 
line no pixel no (pixel units) 
Line no Pixel no Along Across 
track track 
18000.6 | 154.037 | 18000.6 153.967 0 | 0.07 
18164.3 509.96 | 18166.1 507.942 -1.8 | 2.018 
18234.6 507.42 | 18234.2 508.151 0.4 | -0.731 
18216.2 875.47 | 18213.5 874.369 2.7 |: 1.101 
| 18235.6 | 1043.02 | 18234.8 1043.31 0.8 | -0.29 
18247.2 | 1134.07 | 18248.7 1134.07 -1.510 
18285.1 | 1429.53 18285 1429.88 0.1 | -0.35 
18528.4 | 1966.17 | 18529.6 1967.36 -1.2 | -1.19 
185184 | 2135.51 | 185177 2136.15 0.7 | -0.64 
std dev 1.392 | 0.99 
Average 0.022 | -0.001 
  
  
  
  
  
  
  
3.2 Comparison between rational polynomial coefficient 
and physical sensor model 
The ‘step n stare’ mode of image acquisition is an asynchronous 
mode of imaging. It is observed that in this mode of image 
acquisition, the difference between the sensor model derived 
image position and Rational Polynomial Coefficient computed 
image position for same object point is of the order of 0.5 
pixels. 
Third order rational polynomial coefficients are fitted in terrain 
independent mode (Tao, 2002). In this mode the image position 
of a grid of equally spaced ground co-ordinates are computed 
using the physical sensor model. At least 200 points with height 
varying from minimum to maximum value in suitable step size 
are computed. These points are used to fit the rational 
polynomial coefficients. Image position of another set of ground 
points which do not have any point common with the set of 
points used for fitting the rational polynomial coefficients are 
computed using the physical sensor model and rational function 
model. The plot of the difference for near nadir image is shown 
in Fig. 8(a). The RMS error is 0.1244 and 0.090 pixel unit in 
line and pixel direction respectively for near nadir image. 
The plot for image with a view angle of 26 degree is shown in 
Fig. 8(b). The blue line represents the residuals in line direction 
and the red line represents the residuals in pixel direction. The 
RMS error is 0.6910 and 0.5043 pixel unit in line and pixel 
direction respectively. These values are high compared to the 
residuals error between physical sensor derived and RPC 
derived positions for satellite like IRS-P6 where the mode of 
imaging is synchronous (Nagasubramaniam, 2007, Liang, 2006) 
  
    
     
Hesiduaton Near Nadir image 
  
Fig. 8(b) Plot for nadir image 
  
  
  
Residual on Image with26 deg in-track view angle 
2 
estu 
  
  
  
(ird moist 
  
Fig. 8(b) Plot for image with 26 view angle 
Fig. 8 Plot of difference between rational polynomial coefficient 
derived and physical sensor model derived image positions 
3.3 Height Accuracies, Object Modelling and Visualization 
The derived heights along with the building outlines are used 
and orthoimage are used as input for object modelling and 
visualization. Open source software Blender is used for creating 
triangular mesh and adding texture to the building. The texture 
is synthetic and symbolic; it may or may not represent the actual 
structure of the building. Fig. 9 shows a view of the generated 
site model. The height accuracies are evaluated with reference 
to LIDAR data available from Google Earth website. We 
observed that the average error is 0.8m and standard deviation is 
1.8m. 
  
   
Fig. 9 A view of generated site model of portion of Washington 
city 
4. CONCLUSION 
The paper presents an overall schema and results for generation 
of site model from spaceborne multiview/stereo images. The 
results are shown for Cartosat-2 image. The relative orientation 
procedure obviates the need of precise ground control if relative 
measurements are suitable for the desired application. The 
system is designed in a generic way to accommodate images 
from other similar satellites if rational polynomial coefficients 
are available. At present the manual digitization process is 
starting point for capturing the outline of the buildings, this 
process too can be automated as the derived normalized DSM 
represents detection of buildings fairly well. Refinement of 
edges with Canny operator improves the edge localization. 
Geometrically constrained image matching procedure is