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Using direct linear transformation (DLT) method for aerial photogrammetry applications

    Khalid L. A. El-Ashmawy Affiliation
DOI: https://doi.org/10.3846/gac.2018.1629

Abstract

DLT has gained a wide popularity in close range photogrammetry, computer vision, robotics, and biomechanics. The wide popularity of the DLT is due to the linear formulation of the relationship between image and object space coordinates.


This paper aims to develop a simple mathematical model in the form of self calibration direct linear transformation for aerial photogrammetry applications. Software based on the derived mathematical model has been developed and tested using mathematical photogrammetric data.


The effects of block size, number and location of control points, and random and lens distortion errors on self calibration block adjustments using the derived mathematical model and collinearity equations have been studied. It was found that the accuracy of the results of self calibration block adjustment using the derived mathematical model is, to some extent, comparable to the results with collinearity model.


The developed mathematical model widens the application areas of DLT method to include aerial photogrammetry applications especially when the camera interior and exterior orientations are unknown.

Keyword : aerial photogrammetry, DLT, MDLT, self calibration block adjustment, bundle block adjustment

How to Cite
El-Ashmawy, K. L. A. (2018). Using direct linear transformation (DLT) method for aerial photogrammetry applications. Geodesy and Cartography, 44(3), 71-79. https://doi.org/10.3846/gac.2018.1629
Published in Issue
Oct 15, 2018
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Creative Commons License

This work is licensed under a Creative Commons Attribution 4.0 International License.

References

Abdel-Aziz, Y. I., & Karara, H. M. (1971). Direct linear transformation into object space coordinates in close-range photogrammetry. In Proceedings Symposium on Close Range Photogrammetry (pp. 1-18). Urbana, Illinois.

Abdel-Aziz, Y. I., & Karara, H. M. (2015). Direct linear transformation from comparator coordinates into object space coordinates in close-range. Photogrammetry. Photogrammetric Engineering & Remote Sensing, 81(2), 103-107. https://doi.org/10.14358/PERS.81.2.103

El-Ashmawy, K. (1999). A cost-effective photogrammetric system for engineering applications (Doctoral dissertation). Department of Civil Engineering, University of Roorkee, Roorkee, India.

El-Ashmawy, K., & Azmi, M. (2003). Photogrammetric simultaneous and self calibration block adjustments using coplanarity condition. Engineering Research Journal, 87, 85-101.

Ghosh, S. K. (2005). Fundamentals of computational photogrammetry. New Delhi, India: Concept Publishing Company.

Gregory, K. (1998). Special edition using visual C++ 6. Que, USA.

Malik, D. S. (2010). Data structures using C++ (2 nd ed.). USA: Cengage Learing, Inc.

Mikhail, E. M. (1976). Observations and least squares. New York, U.S.A.: IEP-A Dun-Donnelly publishers.

Tommaselli, A. M. G., & Junior, J. M. (2012). Bundle block adjustment of CBERS-2B HRC imagery combining control points and lines. Photogrammetrie - Fernerkundung - Geoinformation, 2, 129-139(11). https://doi.org/10.1127/1432-8364/2012/0107