Photomosaicing and automatic topography generation from stereo aerial photography

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dc.contributor.author Buckley, Craig
dc.date.accessioned 2008-05-16T14:00:25Z
dc.date.available 2008-05-16T14:00:25Z
dc.date.issued 2008-05-16T14:00:25Z
dc.identifier.uri http://hdl.handle.net/2097/790
dc.description.abstract The Autonomous Vehicle Systems Lab specializes in using autonomous planes for remote sensing applications. By developing an inexpensive image acquisition platform and the algorithms to post process the data, remote sensing can be performed at a lower monetary cost with shorter lead times. This thesis presents one algorithm that has shown to be an effective alternative to the traditional Bundle Adjustment (BA) algorithm used for making composite images from many individual overlapping images. BA simultaneously estimates camera poses and visible feature locations from blocks of overlapping imagery, but is computationally expensive. The alternate algorithm (ABA) uses a cost function that does not explicitly include the feature locations. For photographic sets covering large areas, but having overlap only between adjacent photos, the search space and consequently the computational cost is significantly reduced when compared to typical BA. The usefulness of the algorithm is demonstrated by comparing a digital elevation model created through the ABA with LIDAR data. en
dc.description.sponsorship NASA en
dc.language.iso en_US en
dc.publisher Kansas State University en
dc.subject Mapping en
dc.subject Remote Sensing en
dc.subject Photogrammetry en
dc.subject Imaging en
dc.subject Unmanned Aerial Vehicle en
dc.subject Mosaicing en
dc.title Photomosaicing and automatic topography generation from stereo aerial photography en
dc.type Thesis en
dc.description.degree Master of Science en
dc.description.level Masters en
dc.description.department Department of Mechanical and Nuclear Engineering en
dc.description.advisor Dale E. Schinstock, Chris Lewis en
dc.subject.umi Engineering, Mechanical (0548) en
dc.date.published 2008 en
dc.date.graduationmonth May en


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