33, 2012
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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
view are very different. In dense urban area, for instance, the
simultaneous visibility at the street level is highly dependent on
the directions and the incidence angles of the pair of images. In
this context, the expected completeness of the elevation surface
is easily anticipated from the viewing angles, the estimated
buildings heights and streets width.
Regarding the part of the scene visible from both points of view,
the performance of the matching, at image level, depends also
on how different the two points of view are, but this dependence
cannot be theoretically quantified. Many factors are involved in
this process, as the matching algorithm, the morphology and the
texture of the scene, but, from a statistical point of view, we can
say that the matching RMS error E,,, is an increasing function of
the stereoscopic angle @ with E,,(0) > 0.
If we assume that the final 3D measurement error is (roughly)
E,yz() = Em(a)/tana, an optimum angle value may be
found for a given algorithm and a given scene.
If more than two images are available, the previous rule holds
for each pairwise matching. If the matching errors are
statistically independent from one stereo pair to the other, one
can expect an improved accuracy from the merged elevation
measure. Unfortunately, the errors are not always independent
and, even in this case, the well known 1/+/N rule holds only for
the RMS value (not for the 90% error). That is why an
experimental approach is required in order to estimate the actual
accuracy of each combination of viewing angles.
As far as the robustness and the completeness are concerned, a
benefit can be expected from multiple stereo pairs, as long as
the additional viewing angles allow sufficient ground visibility
and resolution.
This work concentrates on the actual 3D performances obtained
from Pleiades images, using various stereoscopic configurations
over various landscapes.
4. OVERVIEW OF THE PROCESSING WORKFLOW
4.1 Bundle adjustment
The attitude biases and drifts of all images are simultaneously
estimated, using a set of ground control points and a large
number of tie points. The high density of the tie points allows
checking the consistency of the data set.
4.2 Pairwise matching
Individual stereo pairs are matched separately at the pixel level,
using a belief propagation algorithm.
4.3 3D measurements merge
When several stereo pairs are available, the corresponding DEM
are merged with a statistically robust criterion, filtering as much
as possible the matching errors.
5. EXPERIMENTAL RESULTS
The following experiments were made during a very early stage
of the Pleiades validation phase, just after the launch. The
interior orientation of the camera was not fully optimised at this
time and the results presented here may not reach the ultimate
accuracy that will be available when the satellite is officially
declared operational. Nevertheless, according to our past
experience, these results might be very close to what can be
expected in the best conditions from the Pleiades specifications.
Stereoscopic images have been acquired in a single pass over
the four following areas:
e Lisboa (2 images)
e Hobart (3 images)
e Montagne Sainte Victoire (2 images)
e Melbourne (17 images)
These sites were previously surveyed with various airborne
cameras during the past twelve years. From the oldest of these
aerial references, Lisboa and Hobart, we could only extract a
few tens of check points. Even if the Melbourne reference is
rather old, we could extract a more significant number of points.
For these three sites, the check points are concentrated in the
dense urban center. The last site, in the south of France is
almost fully covered with a recent 5meter digital terrain model
(DTM). A large number of control points were extracted
exclusively on bare earth to avoid the discrepancy between the
Pleiades DEM and the reference DTM.
The absolute height accuracy of the reference data is estimated
between 0.25 and 0.35 meters, depending on the nature of the
surface (natural or man-made).
The table below summarizes the geometric configurations of the
acquisitions and the final performances measured (in meters) for
the best images combination.
Site Incidences | Nb. Points Bias RMS
Lisboa -4/10 61 0.17 0.58
Hobart -2/10/15 69 0.09 0.58
SteVictoire -13/22 2407 -0.18 0.53
Melbourne -49...--49 295 0.27 0.49
We will now focus on the two opposite situations represented
by Ste Victoire and Melbourne. The first case is a typical
acquisition configuration over an open landscape, with a wide
stereo angle aiming at maximizing the geometric accuracy
without too much care about visibility limitation. The second
case is a nice test bed for experimentation and quantification of
the "stereo dilemma" in a dense urban context.
5.1 Montagne Sainte-Victoire
A single pair was acquired with a rather wide stereo angle,
providing a good accuracy on moderate reliefs. The situation is
more difficult on the south face of the mountain, with a
concentration of very steep slopes. Locally, we noticed losses of
resolution, due to a line of sight nearly tangent to the terrain.
Figure 1 Montagne Sainte Victoire DEM
