3 research outputs found
Minimising systematic error surfaces in digital elevation models using oblique convergent imagery
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
The accuracy of a river bed moulding/casting system and the effectiveness of a low-cost digital camera for recording river bed fabric
Digital photogrammetry has been used to develop and test an artificial
river bed moulding and casting system, which allows the pebbles within a
coarse grain river bed to be recreated for hydraulic research in a laboratory
flow channel or flume. Imagery of both the original streambed and the cast
facsimile was acquired using a non-metric Kodak DCS460 digital camera
and digital elevation models and orthophotographs were derived and
compared to assess the accuracy of the moulding and casting system. These
comparative tests proved to be critical in modifying and developing the
system.
Additional imagery was obtained in the field using a non-metric
Olympus C3030 “compact” digital camera to assess whether far cheaper
camera technology could deliver data appropriate for such comparative
examinations. Internal calibration parameter sets and data that were
generated were compared with data obtained by the non-metric Kodak
DCS460. These tests demonstrate that digital sensors built around highquality
35 mm professional camera bodies and lenses are required for
comparative examinations and for similar system development
Metric capabilities of low-cost digital cameras for close range surface measurement
This paper examines the potential of low cost digital cameras for
close-range surface measurement using feature based image matching
methods. This is achieved through extracting digital elevation models
(DEMs) and comparing accuracies between three low-cost consumer
grade digital cameras (Sony DSC-P10, Olympus C3030, Nikon Coolpix
3100) and the proven Kodak DCS460. Surprisingly, the tests revealed
that the highest accuracies were achieved using the Sony DSC-P10, not
the Kodak DCS460, whilst the other two cameras certainly proved
suitable for most close-range surface measurement tasks. Lens
modelling was found to provide a limiting constraint on final
accuracies, with very small systematic error surfaces caused by residual
imperfections in lens modelling. The IMAGINE OrthoBASE Pro
software and an independent self-calibrating bundle adjustment were
used to process these data. These tests identified an inaccuracy in the
self-calibrating capability of IMAGINE OrthoBASE Pro version 8.6 and
Leica Geosystems LPS 8.7, which will be rectified in subsequent
software releases. The study has demonstrated that cheaper consumer
grade digital cameras have potential for routine surface measurement
provided lens modelling is considered. The lead author is maintaining a
web based repository for camera calibration data, which may assist
other users