COMPARATIVE-ASSESSMENT OF 2 ALGORITHMS FOR CALIBRATING STEREOPHOTOGRAMMETRIC SYSTEMS

In this paper, a comparison is carried out between two photogrammetric algorithms aimed at camera calibration and three-dimensional target point reconstruction by 'absolute' distributions of control points; the first is Marzan and Karara's DLT, the second is CESNO, by the author, an algorithm quite close to Hatze's modified DLT (MDLT). The comparative assessment is especially aimed at testing the capability of the two methods to produce good results when calibration data are to be extrapolated beyond the space spanned by the control distribution. The assessment was carried out not by a real stereophotogrammetric system, but by the computer simulation of a two-camera set-up. Various combinations of internal camera parameters, such as the scaled principal distances, were tried out. As for the magnitude of the simulated non-linear lens distortion, three configurations were used which produced 'low', 'medium' and 'strong' distortion. The influence of decreasing the number of control (calibration) points on the accuracy performance of the two algorithms was also investigated. The results show the superiority of CESNO, especially with medium or strong lens distortion, or when the two camera principal distances sensibly differ.