Istanbul 2004
investigations
on 2 a short
bed. The data
he processing
SETUP
measurement
n setup that
s build up for
jects using a
fa generation
in Section 4.
s depicted in
nulation or a
use of a 3-d
sure 2-1) and
position and
) get a high-
re 2-3). The
d we want to
temporal and
ling the laser
of the laser
gence of the
=
International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences, Vol XXXV, Part B2. Istanbul 2004
laser beam are used for convolving the high-resolution range
image with the temporal waveform and weighting the high-
resolution reflectance image with the spatial energy distribution
(Figure 2-5). The spatial undersampling of the high resolution
data is comparable to focusing the laser beam on the detector of
the receiver (Figure 2-6). This kind of processing generates an
intensity cube where the values correspond to the intensity of
the signal. The simulation should give a realistic description of
what we would expect from the measurement (Figure 2-7).
To improve the estimate of the building's edge position the
intensity cube is processed (data analysis). Processing starts
with the matched filtering for signal preprocessing of the
intensity cube to increase the accuracy of the range
measurement and improve the detection rate (Figure 2-8). Then
cach detected pulse is investigated for characteristic properties
with pulse property extraction to get an enhanced description of
the illuminated surface (Figure 2-9). By the use of the
determined pulse properties a region based segmentation
algorithm generates range and power images for region
descriptions to handle the ambiguity of multiple reflections at
the same spatial position (Figure 2-10). Analyzing the pulse
power in the associated spatial neighborhood of the region
edges estimates the edge position and edge orientation with sub
pixel accuracy (Figure 2-11). Finally, for evaluation the
received parametric boundary function of the region edges has
to be compared with the 3-d object model (Figure 2-12).
3. DATA GENERATION
For simulating the temporal waveform of the backscattered
pulses a scene model (1) and a sensor model (ii) is required.
3.1 Scene modeling
3.1.1 Scene representation
For a 3-d scene representation, our simulation setup considers
geometric and radiometric features of the illuminated surface in
the form of 3-d object models with homogeneous surface
reflectance. Figure 3 shows a 3-d object model with a
homogeneous surface reflectance of the building in Figure |
based on VRML (Virtual Reality Modeling Language).
Figure 3. 3-d object model with homogeneous surface
reflectance
3.1.2 Sampling
The object model with homogeneous surface reflectance is then
ampled higher than the scanning grid we simulate and process,
ecause with the higher spatial resolution we simulate the
spatial distribution of the laser beam. Considering the position
ind orientation of the sensor system we receive a high-
resolution range image (Figure 4) and reflectance image.
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Depending on the predetermined position and orientation of the
sensor system, various range images can be captured.
Figure 4. High-resolution range image
3.2 Sensor modeling
The sensor modeling considers the specific properties of the
sensing process: the position and orientation of the sensor, the
laser pulse description, scanning and the receiver properties.
3.2.1 Orientation
To simulate various aspects a description of the extrinsic
orientation of the laser scanning system with a GPS/INS system
is used.
3.2.2 Laser pulse description
The transmitted laser pulse of the system is characterized by
specific pulse properties (Jutzi et al., 2003a). We assume a
radial symmetric Gaussian spatial distribution and a temporal
exponential function as an approximation for the laser pulse.
3.2.3 Scanning
Depending on the scan pattern of the laser scanner system, the
grid spacing of the scanning and the divergence of the laser
beam a sub-area of the high-resolution range image is
processed. By convolving the sub-area of the range image with
the temporal waveform of the laser pulse, we receive a high-
resolution intensity cube. Furthermore the corresponding sub-
area of the high-resolution reflectance image is weighted with
the spatial energy distribution of the laser beam (Gaussian
distribution at the grid line +26) to take into account the amount
of backscattered laser light for each reflectance value. Then we
have a description of the backscattered laser beam with a higher
spatial resolution than necessary for processing.
3.24 Receiver
By focusing the beam with its specific properties on the
detector of the receiver, the spatial resolution is reduced and
this is simulated with a spatial undersampling of the sub-areas.
Finally we receive an intensity cube that considers the scanning
width of the simulated laser scanner system and the temporal
description of the backscattered signal. Because each
reflectance value in the sub-area is processed by
undersampling, multiple reflections arc considered with the
backscattered signal.