Improving Autonomous Estimates of DEM Uncertainties by Exploiting Computer Matching Asymmetries
Andres Corrada-Emmanuel, University of Massachusetts - Amherst; Brian Pinette, University of Massachusetts - Amherst; Andrey Ostapchenko, University of Massachusetts - Amherst; and Howard Schultz, University of Massachusetts - Amherst
DATE: July 2007
SOURCE: Proceedings of the 8th Conference on Optical 3-D Measurement Techniques
RELATED URL: http://www.photogrammetry.ethz.ch/optical3d/
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ABSTRACT:
We consider the problem of estimating the vertical uncertainty in Digital Elevation Models when results from
asymmetric computer matches are used. The use of asymmetric matches doubles the height estimates available
for creating a fused DEM. But if the asymmetric matches are perfectly correlated the variance would not drop
by a factor of $1/\sqrt{2}$ as they would for uncorrelated measurements. We present an error model that uses
the observed height estimates to measure the average correlation between the asymmetric matches absent any knowledge
of the true heights in the DEM. It requires at least three photographs to autonomously estimate the correlation between asymmetric pairs. Experimental results with a specific set of aerial photographs show that the correlation coefficient varies from $0.5$ to $0.9$. This demonstrates that for any algorithm used
to fuse DEMs from multiple photographs a better result would be obtained by employing the extra information in asymmetric
pairs.