Articles | Volume 11, issue 4
https://doi.org/10.5194/amt-11-2041-2018
© Author(s) 2018. This work is distributed under
the Creative Commons Attribution 3.0 License.
the Creative Commons Attribution 3.0 License.
https://doi.org/10.5194/amt-11-2041-2018
© Author(s) 2018. This work is distributed under
the Creative Commons Attribution 3.0 License.
the Creative Commons Attribution 3.0 License.
High-dynamic-range imaging for cloud segmentation
Soumyabrata Dev
School of Electrical and Electronic Engineering, Nanyang Technological University (NTU), 639798 Singapore
ADAPT SFI Research Centre, Trinity College Dublin, Ireland
Florian M. Savoy
Advanced Digital Sciences Center (ADSC), University of Illinois at Urbana-Champaign, 138602 Singapore
Yee Hui Lee
School of Electrical and Electronic Engineering, Nanyang Technological University (NTU), 639798 Singapore
Stefan Winkler
CORRESPONDING AUTHOR
Advanced Digital Sciences Center (ADSC), University of Illinois at Urbana-Champaign, 138602 Singapore
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Cited
16 citations as recorded by crossref.
- Assessing Cloud Segmentation in the Chromacity Diagram of All-Sky Images L. Krauz et al. https://doi.org/10.3390/rs12111902
- CAU-Net: An attention-based feature enhancement model for ground-based cloud image segmentation applicable to peri-solar regions J. Zhu et al. https://doi.org/10.1016/j.asr.2025.10.048
- Fish-eye camera and image processing for commanding a solar tracker G. Garcia-Gil & J. Ramirez https://doi.org/10.1016/j.heliyon.2019.e01398
- Evaluating Whole-Sky Cloud Segmentation Against an Operating Solar Station: The CLOUD99 Dataset and Protocol H. Wang et al. https://doi.org/10.3390/universe12100291
- LAMSkyCam: A low-cost and miniature ground-based sky camera M. Jain et al. https://doi.org/10.1016/j.ohx.2022.e00346
- BSANet: A Bilateral Segregation and Aggregation Network for Real-time Cloud Segmentation Y. Li et al. https://doi.org/10.1016/j.rsase.2025.101536
- Ultra-short-term photovoltaic power prediction based on ground-based cloud images: A review C. Shi et al. https://doi.org/10.1016/j.apenergy.2025.126943
- Experimental review and recent advances in deep learning techniques for solar irradiance forecasting and prediction C. Otuka et al. https://doi.org/10.1016/j.solener.2025.114175
- Estimating solar irradiance using sky imagers S. Dev et al. https://doi.org/10.5194/amt-12-5417-2019
- HDR Merging of RAW Exposure Series for All-Sky Cameras: A Comparative Study for Circumsolar Radiometry P. Matteschk et al. https://doi.org/10.3390/jimaging11120442
- Using U-Net network for efficient brain tumor segmentation in MRI images J. Walsh et al. https://doi.org/10.1016/j.health.2022.100098
- Enhancing coastal water body segmentation with Landsat Irish Coastal Segmentation (LICS) dataset C. O’Sullivan et al. https://doi.org/10.1016/j.rsase.2024.101276
- Open-source sky image datasets for solar forecasting with deep learning: A comprehensive survey Y. Nie et al. https://doi.org/10.1016/j.rser.2023.113977
- Solar irradiance forecasting meta-review: An in-depth systematic meta-review on solar irradiance forecasting datasets, predictive pipelines and performance F. Mehmood et al. https://doi.org/10.1016/j.rineng.2026.112449
- Recent advances in intra-hour solar forecasting: A review of ground-based sky image methods F. Lin et al. https://doi.org/10.1016/j.ijforecast.2021.11.002
- Semantic segmentation of terrestrial whole-sky images using the new W-Net model with the stationary wavelet transform 2D D. Fantini et al. https://doi.org/10.1016/j.array.2025.100587
16 citations as recorded by crossref.
- Assessing Cloud Segmentation in the Chromacity Diagram of All-Sky Images L. Krauz et al. https://doi.org/10.3390/rs12111902
- CAU-Net: An attention-based feature enhancement model for ground-based cloud image segmentation applicable to peri-solar regions J. Zhu et al. https://doi.org/10.1016/j.asr.2025.10.048
- Fish-eye camera and image processing for commanding a solar tracker G. Garcia-Gil & J. Ramirez https://doi.org/10.1016/j.heliyon.2019.e01398
- Evaluating Whole-Sky Cloud Segmentation Against an Operating Solar Station: The CLOUD99 Dataset and Protocol H. Wang et al. https://doi.org/10.3390/universe12100291
- LAMSkyCam: A low-cost and miniature ground-based sky camera M. Jain et al. https://doi.org/10.1016/j.ohx.2022.e00346
- BSANet: A Bilateral Segregation and Aggregation Network for Real-time Cloud Segmentation Y. Li et al. https://doi.org/10.1016/j.rsase.2025.101536
- Ultra-short-term photovoltaic power prediction based on ground-based cloud images: A review C. Shi et al. https://doi.org/10.1016/j.apenergy.2025.126943
- Experimental review and recent advances in deep learning techniques for solar irradiance forecasting and prediction C. Otuka et al. https://doi.org/10.1016/j.solener.2025.114175
- Estimating solar irradiance using sky imagers S. Dev et al. https://doi.org/10.5194/amt-12-5417-2019
- HDR Merging of RAW Exposure Series for All-Sky Cameras: A Comparative Study for Circumsolar Radiometry P. Matteschk et al. https://doi.org/10.3390/jimaging11120442
- Using U-Net network for efficient brain tumor segmentation in MRI images J. Walsh et al. https://doi.org/10.1016/j.health.2022.100098
- Enhancing coastal water body segmentation with Landsat Irish Coastal Segmentation (LICS) dataset C. O’Sullivan et al. https://doi.org/10.1016/j.rsase.2024.101276
- Open-source sky image datasets for solar forecasting with deep learning: A comprehensive survey Y. Nie et al. https://doi.org/10.1016/j.rser.2023.113977
- Solar irradiance forecasting meta-review: An in-depth systematic meta-review on solar irradiance forecasting datasets, predictive pipelines and performance F. Mehmood et al. https://doi.org/10.1016/j.rineng.2026.112449
- Recent advances in intra-hour solar forecasting: A review of ground-based sky image methods F. Lin et al. https://doi.org/10.1016/j.ijforecast.2021.11.002
- Semantic segmentation of terrestrial whole-sky images using the new W-Net model with the stationary wavelet transform 2D D. Fantini et al. https://doi.org/10.1016/j.array.2025.100587
Saved (final revised paper)
Latest update: 05 Oct 2026
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 overexposed, and the regions near the horizon are underexposed. In this paper, we propose HDRCloudSeg – an effective method for cloud segmentation using high-dynamic-range (HDR) imaging. We describe the entire process and also release a new database.
Sky–cloud images obtained from ground-based sky cameras are usually captured using a fish-eye...