Cloud photogrammetry with dense stereo for fisheye cameras
We present a novel approach for dense 3-D cloud reconstruction above an area of 10 × 10 km<sup>2</sup> using two hemispheric sky imagers with fisheye lenses in a stereo setup. We examine an epipolar rectification model designed for fisheye cameras, which allows the use of efficient ou...
| Main Authors: | , , , , , |
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| Format: | Article |
| Language: | English |
| Published: |
Copernicus Publications
2016-11-01
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| Series: | Atmospheric Chemistry and Physics |
| Online Access: | https://www.atmos-chem-phys.net/16/14231/2016/acp-16-14231-2016.pdf |
| Summary: | We present a novel approach for dense 3-D cloud reconstruction above an area
of 10 × 10 km<sup>2</sup> using two hemispheric sky imagers with fisheye
lenses in a stereo setup. We examine an epipolar rectification model designed
for fisheye cameras, which allows the use of efficient out-of-the-box dense
matching algorithms designed for classical pinhole-type cameras to search for
correspondence information at every pixel. The resulting dense point cloud
allows to recover a detailed and more complete cloud morphology compared to
previous approaches that employed sparse feature-based stereo or assumed
geometric constraints on the cloud field. Our approach is very efficient and
can be fully automated. From the obtained 3-D shapes, cloud dynamics, size,
motion, type and spacing can be derived, and used for radiation closure under
cloudy conditions, for example.<br><br>
Fisheye lenses follow a different projection function than classical
pinhole-type cameras and provide a large field of view with a single image.
However, the computation of dense 3-D information is more complicated and
standard implementations for dense 3-D stereo reconstruction cannot be easily
applied.<br><br>
Together with an appropriate camera calibration, which includes internal
camera geometry, global position and orientation of the stereo camera
pair, we use the correspondence information from the stereo matching for
dense 3-D stereo reconstruction of clouds located around the cameras.<br><br>
We implement and evaluate the proposed approach using real world data and
present two case studies. In the first case, we validate the quality and
accuracy of the method by comparing the stereo reconstruction of a
stratocumulus layer with reflectivity observations measured by a cloud radar
and the cloud-base height estimated from a Lidar-ceilometer. The second case
analyzes a rapid cumulus evolution in the presence of strong wind shear. |
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| ISSN: | 1680-7316 1680-7324 |