Unmanned Aerial Vehicle Path Planning and Image Processing for Orthoimagery and Digital Surface Model Generation
Due to their relatively cheap costs and ability to fly at low altitudes above ground, micro unmanned aerial vehicles are ideal platforms for performing photogrammetric missions above archaeological sites. Advances in image matching and 3D point-cloud generation from 2D images have allowed easier gen...
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ndltd-VANDERBILT-oai-VANDERBILTETD-etd-11302012-1513032013-01-08T17:17:06Z Unmanned Aerial Vehicle Path Planning and Image Processing for Orthoimagery and Digital Surface Model Generation Bailey, Mark Willis Computer Science Due to their relatively cheap costs and ability to fly at low altitudes above ground, micro unmanned aerial vehicles are ideal platforms for performing photogrammetric missions above archaeological sites. Advances in image matching and 3D point-cloud generation from 2D images have allowed easier generation of digital surface models and orthophotographs from images captured by an unmanned aerial vehicle equipped with a high-resolution camera. These digital surface models and orthophotographs are much higher resolution and generated in a timelier manner than those from traditional methods, such as satellites, kites, balloons and total stations. However, current unmanned aerial vehicle systems require a high level of technical knowledge or pilot ability to perform photogrammetric tasks. This thesis seeks to make the entire process of generating digital surface models and orthophotographs simpler, from capturing the images to processing them, by presenting a new path planning algorithm that optimizes over various parameters. Simulations showed that choosing a path, which minimizes the number of flight lines across the site being photographed, by accounting for geometric properties of the site, performs the best, even in the presence of wind. Furthermore, various parameters were explored using Agisofts Photoscan to generate digital surface models and orthophotographs from images captured by an unmanned aerial vehicle flown manually over an archaeological site in Peru. Those experiments with Photoscan revealed several, subjective image quality conditions for guaranteeing better image matching and confirmed that a back-and-forth path produces the best matching and quality of digital surface models and orthophotographs. Julie A. Adams Gautam Biswas VANDERBILT 2012-12-11 text application/pdf http://etd.library.vanderbilt.edu/available/etd-11302012-151303/ http://etd.library.vanderbilt.edu/available/etd-11302012-151303/ en unrestricted I hereby certify that, if appropriate, I have obtained and attached hereto a written permission statement from the owner(s) of each third party copyrighted matter to be included in my thesis, dissertation, or project report, allowing distribution as specified below. I certify that the version I submitted is the same as that approved by my advisory committee. I hereby grant to Vanderbilt University or its agents the non-exclusive license to archive and make accessible, under the conditions specified below, my thesis, dissertation, or project report in whole or in part in all forms of media, now or hereafter known. I retain all other ownership rights to the copyright of the thesis, dissertation or project report. I also retain the right to use in future works (such as articles or books) all or part of this thesis, dissertation, or project report. |
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Computer Science Bailey, Mark Willis Unmanned Aerial Vehicle Path Planning and Image Processing for Orthoimagery and Digital Surface Model Generation |
description |
Due to their relatively cheap costs and ability to fly at low altitudes above ground, micro unmanned aerial vehicles are ideal platforms for performing photogrammetric missions above archaeological sites. Advances in image matching and 3D point-cloud generation from 2D images have allowed easier generation of digital surface models and orthophotographs from images captured by an unmanned aerial vehicle equipped with a high-resolution camera. These digital surface models and orthophotographs are much higher resolution and generated in a timelier manner than those from traditional methods, such as satellites, kites, balloons and total stations. However, current unmanned aerial vehicle systems require a high level of technical knowledge or pilot ability to perform photogrammetric tasks. This thesis seeks to make the entire process of generating digital surface models and orthophotographs simpler, from capturing the images to processing them, by presenting a new path planning algorithm that optimizes over various parameters. Simulations showed that choosing a path, which minimizes the number of flight lines across the site being photographed, by accounting for geometric properties of the site, performs the best, even in the presence of wind. Furthermore, various parameters were explored using Agisofts Photoscan to generate digital surface models and orthophotographs from images captured by an unmanned aerial vehicle flown manually over an archaeological site in Peru. Those experiments with Photoscan revealed several, subjective image quality conditions for guaranteeing better image matching and confirmed that a back-and-forth path produces the best matching and quality of digital surface models and orthophotographs. |
author2 |
Julie A. Adams |
author_facet |
Julie A. Adams Bailey, Mark Willis |
author |
Bailey, Mark Willis |
author_sort |
Bailey, Mark Willis |
title |
Unmanned Aerial Vehicle Path Planning and Image Processing for Orthoimagery and Digital Surface Model Generation |
title_short |
Unmanned Aerial Vehicle Path Planning and Image Processing for Orthoimagery and Digital Surface Model Generation |
title_full |
Unmanned Aerial Vehicle Path Planning and Image Processing for Orthoimagery and Digital Surface Model Generation |
title_fullStr |
Unmanned Aerial Vehicle Path Planning and Image Processing for Orthoimagery and Digital Surface Model Generation |
title_full_unstemmed |
Unmanned Aerial Vehicle Path Planning and Image Processing for Orthoimagery and Digital Surface Model Generation |
title_sort |
unmanned aerial vehicle path planning and image processing for orthoimagery and digital surface model generation |
publisher |
VANDERBILT |
publishDate |
2012 |
url |
http://etd.library.vanderbilt.edu/available/etd-11302012-151303/ |
work_keys_str_mv |
AT baileymarkwillis unmannedaerialvehiclepathplanningandimageprocessingfororthoimageryanddigitalsurfacemodelgeneration |
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