High-dynamic-range imaging for cloud segmentation

Sky–cloud images obtained from ground-based sky cameras are usually captured using a fisheye 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 sc...

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Bibliographic Details
Published in:Atmospheric measurement techniques 2018-04, Vol.11 (4), p.2041-2049
Main Authors: Dev, Soumyabrata, Savoy, Florian M, Lee, Yee Hui, Winkler, Stefan
Format: Article
Language:English
Subjects:
Algorithms
Cameras
Clouds
Clouds (Meteorology)
Digital cameras
Field of view
Fisheye views
Image processing
Image segmentation
Imaging techniques
Lenses
Methods
Properties
Radiance
Visualization
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Summary:Sky–cloud images obtained from ground-based sky cameras are usually captured using a fisheye 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 overexposed, and the regions near the horizon are underexposed. This renders cloud segmentation for such images difficult. In this paper, we propose HDRCloudSeg – an effective method for cloud segmentation using high-dynamic-range (HDR) imaging based on multi-exposure fusion. We describe the HDR image generation process and release a new database to the community for benchmarking. Our proposed approach is the first using HDR radiance maps for cloud segmentation and achieves very good results.
ISSN:1867-8548
1867-1381
1867-8548
DOI:10.5194/amt-11-2041-2018