Markus Niederöst 
  
  
Fig. 3: Orthophoto of the test area Fig. 4: Classification result 
Application of the multichannel classification procedure to the test area (Fig. 3) produced a result which shows a clear 
separation of buildings from other image content (Fig. 4). Although trees close to buildings could not be completely 
eliminated and shapes of buildings are often not accurate, the result is sufficient for being used in further steps. 
In order to provide data which can be used as approximate data for the reconstruction, the classification result is 
processed to get a list of bounding boxes, including one bounding box for each classified building. Those northward 
oriented rectancles serve as input vector data for the building reconstruction. 
4 BUILDING RECONSTRUCTION 
The building reconstruction process is done for 
each initial building seperately. Input for the 
reconstruction can either be the approximate 
vector data provided by L+T (VECTOR25), 
the result from the blob detection or a bound- 
ing box derived from the classification result. 
The building reconstruction steps described 
below are done using image data based on the 
calculated color orthophoto and height infor- 
mation. Those are the degree of artificiality 
(DoA) described in '3.3 Multichannel classifi- 
cation’, the absolute height values from the 
DSM, the normalized DSM and the L* chan- 
nel (brightness) which is used to calculate ori- : 
entation and magnitude of the grey value Fig. 5: 
Used data for building reconstruction: 
gradients using the Sobel operator (Fig. 5). 
a) L* channel (brightness) 
: b) magnitude of grey value gradients (from L*) 
This new approach profits of the fact that a C) orientation of grey value gradients (from L*) 
multiplication of the normalized DSM with the dyrormalized DSM 
degree of artificiality results in a separation of 
artificial objects above ground from all other 
objects. 
e) degree of artificiality (from R and G) 
f) multiplication of the normalized DSM with the 
degree of artificiality 
4.1 Translation 
First step of the building reconstruction is the improvement of the planar position. A binary mask (Streilein, 1999) 
calculated from the approximate vector data is moved on a regular raster (rasterwidth 2.5 m), going from -10 m to 10m 
in x- and y-direction. On each of those 81 positions the following score (Eq. 1) is calculated: 
  
638 International Archives of Photogrammetry and Remote Sensing. Vol. XXXIII, Part B3. Amsterdam 2000. 
  
SC 
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Fig. 7: 
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