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The stereo angle is an important parameter for the deriva-
tion of digital terrain models (DTM) from remotely sensed
image data. It characterizes the different viewing angles
(Fig. 2).
a - stereo angle
Fig. 2 Stereo angle
As reliable experimental investigations are either too
expensive or simply impossible, the value for this parame-
ter mainly is only estimated. Our investigations indicate
that the use of a simulation technique may be the best way
to get a satisfying result.
Such a simulator has been developed in the Institute of
Space Sensor Technology (Reulke, N., 1995; Reulke, R.,
Reulke, N., Jahn, H., 1994). It allows the generation of
image data of a very complex scene, encompassing the
radiating or reflecting surface of a planet, the propagation
of the radiation through the atmosphere and through the
optical components, the conversion of the optical into an
electronic signal, and the signal processing.
The simulator consists of three parts. The first one simu-
lates the geometric properties (like orbit, planet, position of
the sun), the second one includes the radiometric condi-
tions, and the last module takes care of the analogous
electronic part of a camera (Fig. 3).
scene (planet, orbit, sun)
ray tracer
Geometry | : ; |
intersection points with DTM
atmosphere, reflections
Radiometry radiance transport
radiance at the sensor
charges
signal processing
digital image
Camera
Fig. 3 Simulation tool
Algorithms for the data processing can be added. The
application of this simulator gives the opportunity to opti-
mize camera parameters and to define optimal detecting
conditions.
The basic idea was that an optimal stereo angle strongly
depends on the structure of the observed terrain. With the
following procedure our simulation technique makes possi-
ble such an optimization:
With the help of the simulator image data have been ge-
nerated, basing on a digital terrain model obtained from
previous Mars missions. A DTM of the Mars was chosen,
because WAOSS is a Mars-camera. Besides there should
be no limitation regarding other landscapes, the DTM was
changed by different exaggeration factors for our investi-
27
gations.
These images were matched in order to find conjugated
points. A match algorithm of the Technical University of
Munich was used (Heipke, C., 1994), which evaluates the
local image point correlation. The first step is choosing a
number of start points. Outgoing from these start points
the matcher tries to find conjugated points. The result of
this procedure is a file containing the coordinates of the
conjugated points in the image plane.
The knowledge of the location of the conjugated points, of
the simulated flight position and of the viewing direction of
every detector element allows the generation of a new ter-
rain model. This part of the processing cycle yields a more
or less dense net of elevation samples. Elevation values
between these samples are available after an interpolation
procedure.
By comparing both DTM’s a error criterion can be defined.
The analysis of the spatial and temporal dependencies of
this criterion on any parameter of the environment and/or
the camera then enables the adaptation of a camera
parameter to the relevant scientific task (Fig. 4). So an
optimal parameter can be found.
real DTM Simulator
received Matcher &
DTM 3D-Recon-
struction
Fig. 4 Scheme of processing
2. OPTIMIZATION OF THE STEREO ANGLE
Already from the beginning it was predictable that a few
processes should influence the optimal stereo angle. The
most important ones will be outlined.
The relative shift of a certain point in two images is the
decisive measure for the determination of its elevation.
Since there is an absolute error due to the spatial discreti-
zation by the optoelectronic system, the relative error
decreases with an increasing stereo angle (Fig. 5). Accor-
dingly, the whole DTM must become more accurate.
o - stereo angle
Fig. 5 Relative shift of conjugated points in dependence on
different stereo angles
The opposing effects are: The larger the stereo angle, the
bigger the perspective distortions. It means that different
CCD-lines get different impressions of one area (Fig. 6).
International Archives of Photogrammetry and Remote Sensing. Vol. XXXI, Part B1. Vienna 1996