Figure 4: A photomosaic of three photos
the initial approximations for multiphoto matching, we en-
sure the selection of areas of sufficient radiometric variation
which inherently lead to better matching accuracy. In ad-
dition, these areas will most likely correspond to features
of interest in the object space, since gray level variations
are caused by markings on the ground, and changes in ra-
diance and/or surface orientation. The use of least squares
techniques for matching provides the additional advantage
of producing results with objectively estimable accuracy, al-
lowing for the proper assignment of weights. Observations
in windows of low entropy, which are typically susceptible
to erroneous matches can be assigned smaller weights, thus
minimizing their effect in a global solution.
In conclusion, it is obvious that multiple image matching
is an essential tool in digital photogrammetry. The intro-
duction of geometric constraints and its performance in the
object space can contribute to making it more rigorous in
theory and consequently practically improved. Combined
as discussed with already developed modules, such as stere-
omatching, it can fully automate the aerotriangulation pro-
cedure, and significantly assist in upgrading the mapping
process.
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