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Atmospheric Measurement Techniques An interactive open-access journal of the European Geosciences Union

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https://doi.org/10.5194/amt-2017-152
© Author(s) 2017. This work is distributed under
the Creative Commons Attribution 3.0 License.
Research article
27 Sep 2017
Review status
This discussion paper is a preprint. It is a manuscript under review for the journal Atmospheric Measurement Techniques (AMT).
High-Dynamic-Range Imaging for Cloud Segmentation
Soumyabrata Dev1, Florian M. Savoy2, Yee Hui Lee1, and Stefan Winkler2 1School of Electrical and Electronic Engineering, Nanyang Technological University (NTU), Singapore 639798
2Advanced Digital Sciences Center (ADSC), University of Illinois at Urbana-Champaign, Singapore 138632
Abstract. Sky/cloud images obtained from ground-based sky-cameras are usually captured using a fish-eye lens with a wide field of view. However, the sky exhibits a large dynamic range in terms of luminance, more than a conventional camera can capture. It is thus difficult to capture the details of an entire scene with a regular camera in a single shot. In most cases, the circumsolar region is over-exposed, and the regions near the horizon are under-exposed. This renders cloud segmentation for such images difficult. In this paper, we propose HDRSeg – an effective method for cloud segmentation using High-Dynamic-Range (HDR) imaging based on multi-exposure fusion. We describe the HDR generation process and release a new database to the community for benchmarking. Our proposed approach is the first using HDR images for cloud segmentation and achieves very good results.

Citation: Dev, S., Savoy, F. M., Lee, Y. H., and Winkler, S.: High-Dynamic-Range Imaging for Cloud Segmentation, Atmos. Meas. Tech. Discuss., https://doi.org/10.5194/amt-2017-152, in review, 2017.
Soumyabrata Dev et al.
Soumyabrata Dev et al.
Soumyabrata Dev et al.

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Short summary
Sky/cloud images obtained from ground-based sky-cameras are usually captured using a fish-eye lens with a wide field of view. However, the sky exhibits a large variation in the scene luminance. In most cases, the circumsolar region is over-exposed, and the regions near the horizon are under-exposed. In this paper, we propose HDRSeg – an effective method for cloud segmentation using High-Dynamic-Range (HDR) imaging. We describe the entire process and also release a new database to the community.
Sky/cloud images obtained from ground-based sky-cameras are usually captured using a fish-eye...
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