High-precision image matching for digital terrain model generation

Abstract

The Adaptive Least Squares Correlation (ALSC), combining gray-level correlation with geometric conditions, was applied to a grid-sampling mode for generation of Digital Terrain Models (DTM) from aerial stereo models.

The heights of targets of different geometric and contrast quality in large-scale digitized images were determined using this technique and compared to results from manual measurements. Both solutions showed an average difference of 0.016–0.038% and a maximum differences of 0.037–0.120% flying height (hg), depending on the height approximation. Most cases investigated required an initial height approximation at the 1–2% hg level. An average height error of 0.2% hg was cleared in each iteration step. The constraints imposed proved to define the movement of the gray-level image patches, thus limiting the search area and probability of false correlation, and increasing the precision and reliability of height determination.