Minimising systematic error surfaces in digital elevation models using oblique convergent imagery
journal contributionposted on 31.10.2011 by Rene Wackrow, Jim H. Chandler
Any type of content formally published in an academic journal, usually following a peer-review process.
There are increasing opportunities to use consumer-grade digital cameras, particularly if accurate spatial data can be captured. Research recently conducted at Loughborough University identified residual systematic error surfaces or domes discernible in digital elevation models (DEMs). These systematic effects are often associated with such cameras and are caused by slightly inaccurate estimated lens distortion parameters. A methodology that minimises the systematic error surfaces was therefore developed, using a mildly convergent image configuration in a vertical perspective. This methodology was tested through simulation and a series of practical tests. This paper investigates the potential of the convergent configuration to minimise the error surfaces, even if the geometrically more complex oblique perspective is used. Initially, simulated data was used to demonstrate that an oblique convergent image configuration can minimise remaining systematic error surfaces using various imaging angles. Additionally, practical tests using a laboratory testfield were conducted to verify results of the simulation. The need to develop a system to measure the topographic surface of a flooding river provided the opportunity to verify the findings of the simulation and laboratory test using real data. Results of the simulation process, the laboratory test and the practical test are reported in this paper and demonstrate that an oblique convergent image configuration eradicates the systematic error surfaces which result from inaccurate lens distortion parameters. This approach is significant because by removing the need for an accurate lens model it effectively improves the accuracies of digital surface representations derived using consumer-grade digital cameras. Carefully selected image configurations could therefore provide new opportunities for improving the quality of photogrammetrically acquired data.
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