Here we present a new method for using existing Digital Elevation Model
(DEM) data to optimize performance of stereo-matching algorithms for
digital topographic determination. We show that existing DEM data, even
those of a poor quality (precision, resolution) can be used as a means
of training stereo-matching algorithms to generate higher quality DEM
data. Existing data are used to identify and to remove cross surface
errors. We test the method using true vertical aerial imagery for a UK
upland study site. Results demonstrate a dramatic improvement in data
quality even where DEM data derived from topographic maps are adopted.
Comparison with other methods suggests that using existing DEM data
improves error identification and correction significantly. Tests
suggest that it is applicable to both archival and commissioned aerial
imagery.