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Extended collinearity equations as derived by the 
authors (see Konecny, Schuhr, 1986) can be 
considered as universal projection equations, 
independent from the sensor. 
Linearized collinearity equations allow to derive 
polynomial equations of equivalent content, which 
are valid under particular flight ^ behaviour 
assumptions. The principal idea of this formulation of 
algorithms goes back to Baker ( 1975 ), who applied 
it on line scanner imagery, which has been extended 
into an universal approach to solve problems of 
image geometry for any remote sensing imagery. In 
addition this approach allows to calculate variations 
in the sensor behaviour, in particular by calculating 
for the "real flight path", as gained from 
housekeeping GPS and by additional parameters , to 
fit smoother to the ground control point field. 
As compared to heuristic approaches, which are still 
in use even for very advanced image processing 
devices, arbitrariness is subdued and the 3rd 
dimension can be calculated. The polynomial 
approach as derived from equivalent collinearity 
equations, successfully has been applied for recent 
remote sensing campaigns. 
To use the advantages of existing bundle block 
adjustment software for conventional photography, 
an approximate transformation of the remote sensing 
image geometry into the conventional image 
geometry and vice versa also successfully has been 
carried out by modifying the BINGO- program of the 
Institute for Photogrammetry of the University of 
Hannover. 
In addition, the following method gives an example 
for a combined approach between parametric and 
non-parametric solutions: image coordinates for 
ground coordinates of particular points with known 
object coordinates , including output pixels (e.g., 
anchor points), can be calculated from known ground 
control points . Supposing, roll-, pitch- and yaw- 
values are neglect able and under the condition, the 
object coordinate system and the image coordinate 
system are in parallel, the valid equations become 
relatively simple. The results improve by applying 
this approach onto several ground control points. The 
deviations of the resulting image coordinate pair can 
be reduced by the weighted mean approach. To apply 
this method, a great amount of ground control points 
is needed, which can be determined by block 
adjustment etc.. 
289 
3. INTRODUCTION OF 
ORTHOPHOTOS 
DIGITAL 
For tasks, which require map accuracy, like 
- GIS-input 
- mosaicing, 
- multisensor imagery and 
- change detection etc., 
for hilly and mountainous terrain, a digital geometric 
pixel by pixel image restitution, including terrain 
height effects is needed. 
To handle larger output blocks and to calculate for 
regional or even particular pixel wise terrain heights, 
a particular method for digital image rectification has 
been established, according to suggestions of Egels 
and Massou d'Autume of the IGN (France) and 
Konecny (1985):For minimum and for maximum 
terrain height the image coordinates of the output 
pixels continuously are determined by bilinear 
interpolation within the corresponding output pixel 
block defined by 4 corresponding anchor points. The 
proper imagecoordinates of the output pixels are 
calculated from linear interpolation in between the 
image coordinates, using the actual terrain-height as 
the argument for interpolation. 
The orthophoto derived, may also be generated with 
a digitally determined coordinate grid, as well as 
edge or gradient enhancement procedures may be 
utilised to generate quasi line maps. In order to verify 
a reliable 
geocoding of remote sensing imagery for, e.g., GIS- 
input, the digital data is transformed into the GIS- 
coordinate system, which includes absolute 
positioning, north orientation and a uniform scale. 
The DEM- influences are already rectified, as well as 
changes in attitudes. 
4. REFERENCES 
Baker, S.R. and Mikhail, E. M., 1975: Geometric 
Analysis and Restitution of Digital Multispectral 
Scanner Data Arrays. The LARS, Purdue University, 
West Lafayette, Indiana. 
Konecny, G., Schuhr, W., Engel, H. and Lohmann, 
P., 1984: Topographic Mapping from Space Borne 
Metric Camera Imagery. In: International Arch. f. 
Photogr. and R.S., Vol. XXV, Part A4, pp. 157-161. 
Konecny, G. ,Schuhr, W. ,Engel, H. ,Lohmann, P. 
Schüring, A. and Wu, J.,1984: Investigation of 
Metric Camera Data Quality, Intern. Arch. f. 
Photogr. +R.S., Vol. XXV, Part Al, pp.64-69. 
Konecny, G. and Schuhr, W., 1985: Linemap 
production with Metric Camera Data. ESA 
Symposium Proceedings, SP-233, pp. 69-73. 
Kruck, E. and LOHMANN, P., 1986: Aerial 
Triangulation of CCD Line-Scanner Images, ESA 
Symposium Proceedings.