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A Four-Step Ortho-Rectification Procedure for Geo-Referencing Video Streams from a Low-Cost UAV
Abstract:In this paper, we present a four-step ortho-rectification procedure for real-time geo-referencing of video data from a low-cost UAV equipped with a multi-sensor system. The basic procedures for the real-time ortho-rectification are: (1) decompilation of the video stream into individual frames; (2) establishing the interior camera orientation parameters; (3) determining the relative orientation parameters for each video frame with respect to each other; (4) finding the absolute orientation parameters, using a self-calibration bundle and adjustment with the aid of a mathematical model. Each ortho-rectified video frame is then mosaicked together to produce a mosaic image of the test area, which is then merged with a well referenced existing digital map for the purpose of geo-referencing and aerial surveillance. A test field located in Abuja, Nigeria was used to evaluate our method. Video and telemetry data were collected for about fifteen minutes, and they were processed using the four-step ortho-rectification procedure. The results demonstrated that the geometric measurement of the control field from ortho-images is more accurate when compared with those from original perspective images when used to pin point the exact location of targets on the video imagery acquired by the UAV. The 2-D planimetric accuracy when compared with the 6 control points measured by a GPS receiver is between 3 to 5 metres.
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 M. Kontitsis, M., Valavanis, K., N. Tsourveloudis , “A UAV Vision System for Airborne Surveillance,” In Proc. of the IEEE International Conference on Robotics and Automation, 2004, pp. 77–83.
 D.W. Casbeer, D.B. Kingston, R.W. Bear , T.W. McLain, and S.M. Li, “Cooperative Forest Fire Surveillance Using a Team of Small Unmanned Air Vehicles.”, Intl. Journal of System Science, January 2005, pp 1-18.
 B.O. Olawale, C.R. Chatwin, R.C.D. Young, P.M. Birch, F.O. Faithpraise and A.O. Olukiran, “Real-Time Monitoring Of Buried Oil Pipeline Right-Of-Way for Third-Party Incursion”, International Journal of Innovative Science, Engineering & Technology, Vol. 2 Issue 2,February 2015, pp. 163-173.
 B. Colfman, M. McCord, and K. Redmill, “Surface Transportation Surveillance from Unmanned Aerial Vehicles” Proc. Of the 83rd Annual Meeting of the Transportation Research Board, 2004.
 J. Allen, and B. Walsh, “Enhanced Oil Spill Surveillance, Detection and Monitoring through the Applied Technology of Unmanned Air Systems”. In: Proceedings of the 2008 international oil spill conference.
 R. W. Beard, T. W. McLain, D. B. Nelson, D. Kingston, and D. Johanson, “Decentralized cooperative aerial surveillance using fixedwing miniature UAVs,” Proc. IEEE, July 2006, vol. 94, no. 7, pp. 1306– 1323.
 Fransaer, D., Vanderhaeghen, F., Everaerts, J., “PEGASUS: Business Plan for a Stratospheric Long Endurance UAV System for Remote Sensing”. The International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences, Istanbul, Turkey, GITC, Lemmer, Netherlands, 2004.
 A. Ollero, J. Ferruz, F. Caballero, S. Hurtado, L. Merino, “Motion Compensation and Object Detection for Autonomous Helicopter Visual Navigation in the Comets System”. In: Proc. of the IEEE International Conference on Robotics and Automation, 2004, pp. 19–24.
 Anon, “Functional Specification for a Satellite Surveillance System”, Andrew Palmer and Associates Report NR01003, March 2001.
 . M.D.F Bento, “Unmanned Aerial Vehicles: An Overview. Inside GNSS “, February, 2008, pp. 54-61.
 N. Mohamed, I. Jawhar, “A Fault-Tolerant Wired/Wireless Sensor Network Architecture or Monitoring Pipeline Infrastructures”, in Proc. Int. Conference on Sensor Technologies and Applications (SENSORCOMM 2008), Cap Esterel, France,25–31 August 2008; pp. 179-184.
 Y. DU, P.M. Teillet, and J.Cihlar, “Radiometric Normalization of Multi- Temporal High-Resolution Satellite Images with Quality Control for Land Cover Change Detection: Remote Sensing of Environment”, 2002, pp. 123–134,
 S. Chen, B. Mulgrew, and P. M. Grant, “A Clustering Technique for Digital Communications Channel Equalization Using Radial Basis Function Networks,” WASET Trans. Neural Networks, vol. 4, pp. 570– 578, July 1993.
 B. Horn Robot Vision, MIT Press, 1986, pp 314 – 315.
 K. Kobayashi, C. Mori, “Relations between the Coefficients in the Projective Transformation Equations and the Orientation Element of the Photograph”. Journal of Photogrammetric Engineering and Remote Sensing. Vol. 63, No. 9, September 1997, pp.1121-1127.
 Z. Li, J. Chen, and E. Baltsavias. Advances in Photogrammetry, Remote Sensing and Spatial Information Sciences, 2008 ISPRS Congress Book. CRC Press, Taylor & Francis Group, Boca Raton, London, New York, Leiden, p. 527.
 E.M Mikhail, J.S. Bethel, J.C. McGlone. Introduction to Modern Photogrammetry. John Wiley & Sons Inc., New.
 http://www.dji.com/product/spreading-wings-s800/spec (Accessed: 11 July 2013).
 Z. Guoqing, ‘’Near Real-Time Orthorectification and Mosaic of Small UAV Video Flow for Time-Critical Event Response’ ’in Proc. o Geoscience and Remote Sensing, IEEE, 47(3), March 2009.
 Y. I. Abdel-Aziz and H. M. Karara, “Direct Linear Transformation from Comparator Coordinates into Object Space Coordinates in Close-Range Photogrammetry,” in Proc. Symp. Close-Range Photogrammetry, Falls Church, VA, 1971, pp. 1–18, Amer. Soc. of Photogrammetry.
 J. Skaloud, M. Cramer, and K. P. Schwarz, “Exterior Orientation by Direct Measurement of Camera and Position,” in Proc. Int. Archives Photogrammetry Remote Sens., Vienna, Austria, 1996, vol. XXXI, pp. 125-130, Part B3.
 Gomarasca, Mario A. Basics of Geomatics. Dordrecht: Springer, 2009. Print.