Abstract
Abstract. Large format digital aerial cameras are now in widespread commercial operation. Despite the advantages of the new cameras over their traditional film counterparts, systematic image errors have been observed in all existing large format digital cameras. Organizations such as the USGS and EuroSDR have therefore focused efforts on calibration, validation and certification of digital camera systems. However, to-date, few studies have assessed the effects of extreme temperature and humidity variations on these camera systems, and the potential for self-calibration in this respect. This research addresses these issues through investigation of the UltraCamD, with test data acquired over a range of climatic zones in Libya. This presentation will report the preliminary results of self-calibration using a bundle block adjustment for an UltraCamD system, based upon aerial data acquired for two test sites during a single field campaign. The datasets were flown at two different flying heights and incorporate differing block geometries. A SOCET SET (v5.4.1) digital photogrammetric workstation was used to triangulate the imagery with investigation of different tie point densities. Following this, a self-calibrating bundle block adjustment was performed using the BLUH software provided by the University of Hannover. Initial testing investigated the influence of tie point density and different coordinate systems and datums on the bundle adjustment results. Further testing was then performed within BLUH in order to determine the optimal set of additional parameters, compensating for systematic image errors and impact upon object space coordinates of independent check points and ground control points.
Highlights
Due to the apparent advantages of digital cameras over conventional film cameras in geometry and image quality, digital cameras are in widespread commercial use
Despite the precision and accuracy of the measurements provided by laboratory calibration, practical tests have shown that without self calibration, systematic image errors are clear for all existing large format digital cameras (Alamus, 2006; Honkavarra, 2006; Kruck, 2005; Passini et al, 2008; Scholz et al, 2009)
Systematic errors which represent the difference between the mathematical model of the perspective geometry and the real image geometry can be detected and respected by self-calibration with additional parameters
Summary
Due to the apparent advantages of digital cameras over conventional film cameras in geometry and image quality, digital cameras are in widespread commercial use. Despite the precision and accuracy of the measurements provided by laboratory calibration, practical tests have shown that without self calibration, systematic image errors are clear for all existing large format digital cameras (Alamus, 2006; Honkavarra, 2006; Kruck, 2005; Passini et al, 2008; Scholz et al, 2009). It has been reported in the literature that the reasons for these errors are due to the differences between the laboratory and the actual mission environment, atmospheric refraction (Tachibana et al, 2008), multi-head integration (Dorsel et al, 2007) and changes in the operating temperature (Yastikli, 2004). Practical tests have shown that even the special additional parameters which are designed to account for the specific geometry of the new digital large format cameras sometimes have limited effects and have not been found to improve accuracy at independent check points. (Baz et al, 2006; Büyüksalih et al, 2006; Jacobsen, 2007)
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