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Proceedings Paper

Accuracy analysis of exterior orientation elements on vertical parallax in POS-supported aerial photogrammetry
Author(s): Zhenli Wu; Xiuxiao Yuan
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Paper Abstract

This paper analyzes the effect of exterior orientation elements on vertical parallax, especially using the orientation parameters of aerial images obtained by a POS (Positioning and Orientation System) after calibration. Firstly, based on the theory of analytical relative orientation of consecutive photo connection, the exterior orientation elements can be easily translated to relative orientation elements. Then, the formula of vertical parallax can be deduced. The results of vertical parallax in left image space coordinate system are compared with the results calculated in the image coordinate system which are parallel to those of the object coordinate system. The validity and feasibility of the mathematical model are tested using two sets of actual data at different images scales. Finally, the differences between the effects of exterior orientation parameters on vertical parallax are compared using exterior orientation parameters obtained by traditional bundle block adjustment and by a POS after calibrated. And how the single element of exterior orientation effected on vertical parallax and how they worked together are analyzed. The empirical results indicate that the effects of different elements of exterior orientation on vertical parallax are different, all exterior orientation parameters can be affected by each other, so the overall effect of vertical parallax accuracy can be restricted by all exterior orientation parameters.

Paper Details

Date Published: 15 October 2009
PDF: 8 pages
Proc. SPIE 7492, International Symposium on Spatial Analysis, Spatial-Temporal Data Modeling, and Data Mining, 74923V (15 October 2009); doi: 10.1117/12.838417
Show Author Affiliations
Zhenli Wu, Wuhan Univ. (China)
Xiuxiao Yuan, Wuhan Univ. (China)

Published in SPIE Proceedings Vol. 7492:
International Symposium on Spatial Analysis, Spatial-Temporal Data Modeling, and Data Mining
Yaolin Liu; Xinming Tang, Editor(s)

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