Abstract
AbstractThe objective of the proposed approach is to locate and measure ground control points in aerial images when large image search spaces are defined due to the use of inaccurate initial exterior orientation parameters, such as those provided by consumer‐grade navigation systems. Vertical terrestrial image patches covering control point areas are generated and compared with aerial patches using feature‐ and area‐based matching algorithms to automatically determine their corresponding positions in aerial images with sub‐pixel precision. The approach is based on techniques for both image search space reduction and adaptive least squares matching. Experiments with real data were performed with bundle block triangulation and the results were analysed using control and check points in both object and image spaces. The proposed technique enabled a significant reduction in the search space within which it was feasible to successfully locate control points. Compared with manual measurements, the results obtained by the automatic technique were more accurate, achieving one‐fifth of the ground sample distance in planimetric check point discrepancies.
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