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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.