International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences, Vol XXXV, Part B4. Istanbul 2004
Figure 6 gives a typical example of the effects of the post-
processing operations. It demonstrates the necessity of both,
the choice of elevation data for delineating buildings rather
than image data (where shadows often extend or falsify the
outline; indicated by the upper arrow), and the dilation
operation which leads to a rather good coincidence with
manually digitised edges. However, remaining errors occur
which are mainly due to the input data quality (indicated by the
lower arrow). It has to be noted that so far only few and simple
post-processing operations have been applied.
5. CONCLUSIONS
Multi-sensor data yield the advantage of producing more scene
features, however, the crucial point in the interpretation
workflow is still the big, application dependent gap between
these features and the related object characteristics. Hence, the
central goal of this contribution was to present a methodology
that bridges this gap for an important application, the
extraction of topographic surface edges with the emphasis on
building edges. In contrast to other methodologies for object
edge extraction we propose an algorithm into which several
features of both, the multiple reflections of the laser scanning
system and the multi-spectral imagery, have been introduced.
With that not only geometrical but also semantical information
are used. As we concentrate on the derivation of building
edges, we applied a region growing algorithm, which by-
passes the problem of linking detected edge pixels to
connected lines.
So far we have presented first qualitative results of our
approach. It could be shown that the simultaneous usage of
geometrical and semantical information definitively improves
the classification and delineation of object edges compared to
the single use of only one source. However, we have still to
state some imperfect results which are mainly due to the
quality of the input data in terms of the point density of the
laser scanning elevations and the image acquisition date which
has led to rather less predictive NDVI values.
In future several improvements of the methodological
components will be addressed. For instance, we will apply a
multi-scale segmentation instead of the use of a single segment
layer. Additionally, the edge image matching process will be
further developed by introducing even more features. Finally,
the methodology will be extended in order to extract further
surface edge classes (like embankments or ditches).
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ACKNOWLEDGEMENTS
Presented data are courtesy of TopoSys GmbH -
(www.toposys.com).
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