Full text: XVIIIth Congress (Part B3)

      
    
   
     
     
   
   
    
   
    
    
  
  
   
   
     
   
    
  
    
     
    
     
   
    
   
   
   
  
  
  
  
   
  
    
  
   
    
    
    
   
  
    
    
  
    
     
    
   
   
   
    
    
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ent with the 
The result of matching is a list of points which are 
consistent with the object model and quality measures of 
the fit between data and model. A final quality check shall 
make sure that an adequate model has been used. A bad 
fit of the measured points to the object model might 
indicate that a wrong object model was used. In this case, 
another model should be selected. Both generation and 
evaluation of correspondence hypotheses are the main 
topics of research work in our concept. 
3.2 Feature Extraction 
Many feature based matching algorithms for photo- 
grammetric surface reconstruction use the Fórstner 
operator to extract distinct points from digital images 
(Krzystek, 1995). On a symbolic level, the image is then 
described by an unstructured cluster of such point 
features. Evidently, a considerable amount of information 
contained in the images is thrown away. We think that 
this information, e.g. line information, but also 
information about the mutual relations between the 
extracted features, should be used in order to increase 
the reliability of a matching algorithm. 
We thus want to use the more complex image model 
proposed in (Fuchs et al., 1995) which was originally 
designed for automatic building extraction. In this model, 
the ideal image is assumed to be composed of 
homogeneous segments, piecewise smooth boundary 
lines of these segments and points. The digital image is a 
blurred and sampled version of the ideal image which is 
additionally afflicted by noise. Thus one can no longer 
speak of finding lines and points in the image, but more 
reasonably of regions containing line segments or points 
(figure 4a); (Fuchs et al., 1995). 
  
  
  
  
  
  
Figure 4: Image regions (a) and region adjacency 
graph with direct (full lines) and indirect (dotted lines) 
neighbourhood relations (b); adopted from 
(Fuchs et al, 1995) 
Each pixel can be classified as belonging either to a 
homogeneous region S, to a region P containig a point or 
to a region L containing a line (figure 4a) using a 
measure for homogeneity and a measure for isotropy of 
texture, both of which can be derived from a local function 
of the grey levels. From a segmentation of the classified 
image, all regions are extracted and a region adjacency 
graph is created which describes the topological relations 
between neighbouring regions (figure 4b); (Fuchs et al., 
1995). 
At the same time as the region adjacency graph is 
created, attributes can be assigned to the extracted 
regions such as the subpixel position of points, the 
average grey level of homogeneous regions, curve 
parameters, e.g. spline coefficients, 'for lines, etc. These 
attributes will become very important for the creation of 
695 
International Archives of Photogrammetry and Remote Sensing. Vol. XXXI, Part B3. Vienna 1996 
correspondence hypotheses. As the subpixel estimates 
for point coordinates (and, perhaps, in a future step, 
curve parameters of lines) will be essential for the 
description of the object, we refer to the region adjacency 
graph as ‘feature adjacency graph’ although it also 
contains homogeneous regions. 
3.3 Image Geometry 
Many matching algorithms use epipolar images, e.g. 
(Gulch, 1994); (Krzystek, 1995). In case epipolar images 
are used, the matching problem can be reduced to a one- 
dimensional problem. This strategy considerably reduces 
the complexity of the matching algorithm. However, in our 
concept we do not use epipolar images for mainly three 
reasons: 
e By using epipolar images, one is restricted to using 
stereo image pairs for matching. We eventually want 
to use more than two images for that purpose. 
e Small errors in the orientation parameters of the 
images might deteriorate the matching result, 
especially when lines which are almost parallel to the 
epipolar lines are used. 
e Epipolar images are derived from the original images 
by resampling. Feature extraction may be influenced 
by the lowpass characteristics of resampling methods. 
Instead of using epipolar images, we will rely on bundle 
block geometry. The bundle block adjustment system 
ORIENT (Kager, 1989) will be integrated into the 
matching software to be developed. Bundle block 
geometry will be used to establish geometrical constraints 
as well as for the formulation of models for the local 
object surface. 
3.4 Generation and Evaluation of Correspondence 
Hypotheses 
The generation of hypotheses for the correspondence of 
features from different images is based on some measure 
of similarity between these features. This similarity 
measure is based on the comparison of the feature 
attributes which have been extracted. If the viewing 
directions are nearly parallel, the correlation coefficient of 
the grey levels in a small region surrounding the point can 
additionally be used as a similarity measure. We also use 
the feature adjacency graph for that purpose because we 
assume that a correspondence between features from 
different images is more likely if the neighbouring image 
regions also show similar attributes (Zhang et al, 1992). 
Up to now, we have not yet decided which feature 
attributes will be used and how the similarity measure 
shall be composed. These questions are among the main 
topics of our research. 
By just using similarity as a criterion for the generation of 
hypotheses, one would get too many wrong hypotheses. 
The number of initial hypotheses is reduced in two ways: 
e Introduction of geometrical constraints: Only features 
with image residuals smaller than a certain threshold 
may correspond to the same object point. 
e Reduction of search space by approximate values. 
The algorithm is successively applied to relatively 
small homologous image patches which are extracted 
according to the approximate values. Additionally, 
thresholds for local height differences can be 
introduced.
	        
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