The International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences. Vol. XXXVII. Part B4. Beijing 2008
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3.6 True 3D Filtering
Filtering must be used to eliminate mismatched points. Such
filtering is a classification in correctly matched points. Often,
the filtering is performed using an interpolation of the terrain
surface because the end product is a DTM. Thus MATCH-T has
used a finite element interpolation in order to filter the point
cloud. This interpolation describes a 2.5D surface. The finite
element filtering has to choose one Z value for one X,Y
coordinate pair. It is well suited for DTM extraction but the real
world is 3D. This method cannot be used to extract 3D Surface
Models (3DSM): the extracted point cloud of MATCH-T DSM
delivers a true 3D representation (figure 1.).
Figure 2. Filtered MATCH-T DSM point cloud distribution
The new filtering algorithm of MATCH-T DSM works in 3D
and can select more than one Z for one X,Y coordinate pair. A
statistical analysis recognizes points with high redundancy and
then selects those with the best accuracy. The filtering realizes
both a noise and data reduction without loss of information.
3.7 Point distribution
Figure 2 illustrates the 3D point distribution. One can recognize
that the distribution is similar to an image that has been
processed with an edge detection operator. Indeed, as MATCH-
T DSM uses the Forstner operator to extract points, this point
distribution is as expected.
After the point filtering the distribution is more regular but
areas with poor textures are still easy to recognize.
4. CASE STUDIES
INPHO has made two case studies using different digital
camera geometries and different GSDs. The goals have been to
determine the accuracy, the completeness and the reliability of
the MATCH-T 3DSM point cloud. In each case, the analysis
has been made with high resolution images, the image
orientation parameters have been determined by
aerotriangulation.
4.1 Case Study 1: 80/30 compare to 80/60 Overlap
This case study compares the quality of DSMs extracted from
two project configurations using the same imagery. The project
with 80/30 overlap has been derived from the 80/60 project by
omitting each second strip.
The information about the project can be found in the table 1.
Type of terrain
Urban
Camera
Ultra CAMD
GSD
7cm
Spectral
characteristics
Panchromatic image
DSM representation
3D point cloud
Number of Control
points on the ground
287
Number of Control
points off ground
341
Table 1. Input information of case study 1
The result summarized in the table 2 shows clearly the benefit
of the higher side overlap. The amount of extracted points is
twice, the final point density is almost 50% higher. With a
completeness of 93% the DSM covers effectively the complete
surface. Only poor textured areas are not covered. The precision
is significantly better and the mean Z offset is considerably
reduced. Thanks to the high resolution images, the point density
is very high. Such a point density for photogrammetric products
is unconventional and opens new fields of research and
applications.
Overlap
80/30
80/60
Number of
extracted points
264 538 105
554 846 130
Number of points
after the filtering
13 828 673
19268617
Density
11,93 pts/m 2
16,62 pts/m 2
Completeness of a
50 cm Raster
85,6%
92,9%
Percent of
validated points
97%
97%
Standard deviation
of control points
12,5cm
10cm
Mean Z shift
-6,5 cm
-2,2 cm
Table 2. Summary of the results of case study 1