Articles | Volume 10, issue 3
https://doi.org/10.5194/amt-10-1191-2017
© Author(s) 2017. 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-10-1191-2017
© Author(s) 2017. This work is distributed under
the Creative Commons Attribution 3.0 License.
the Creative Commons Attribution 3.0 License.
Research article
| 
29 Mar 2017
Research article |
| 29 Mar 2017
An RGB channel operation for removal of the difference of atmospheric scattering and its application on total sky cloud detection
Jun Yang
CORRESPONDING AUTHOR
State Key Laboratory of Severe Weather, Chinese Academy of
Meteorological Sciences, Beijing 100081, China
Atmospheric Sciences Research Center, State University of New York,
Albany, NY 12203, USA
Qilong Min
CORRESPONDING AUTHOR
Atmospheric Sciences Research Center, State University of New York,
Albany, NY 12203, USA
Weitao Lu
State Key Laboratory of Severe Weather, Chinese Academy of
Meteorological Sciences, Beijing 100081, China
Ying Ma
State Key Laboratory of Severe Weather, Chinese Academy of
Meteorological Sciences, Beijing 100081, China
Wen Yao
State Key Laboratory of Severe Weather, Chinese Academy of
Meteorological Sciences, Beijing 100081, China
Tianshu Lu
State Key Laboratory of Severe Weather, Chinese Academy of
Meteorological Sciences, Beijing 100081, China
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Cited
15 citations as recorded by crossref.
- Cloud detection method using ground-based sky images based on clear sky library and superpixel local threshold Y. Niu et al. 10.1016/j.renene.2024.120452
- Pixel‐Based Image Processing for CIE Standard Sky Classification through ANN D. Granados-López et al. 10.1155/2021/2636157
- A Cloud Detection Algorithm with Reduction of Sunlight Interference in Ground-Based Sky Images X. Li et al. 10.3390/atmos10110640
- Retrieval of Oceanic Total Precipitable Water Vapor and Cloud Liquid Water from Fengyun-3D Microwave Sounding Instruments Y. Han et al. 10.1007/s13351-021-0084-4
- Characteristics of Surface Solar Radiation under Different Air Pollution Conditions over Nanjing, China: Observation and Simulation H. Luo et al. 10.1007/s00376-019-9010-4
- Diurnal and nocturnal cloud segmentation of all-sky imager (ASI) images using enhancement fully convolutional networks C. Shi et al. 10.5194/amt-12-4713-2019
- Single image dehazing using a new color channel G. Sahu et al. 10.1016/j.jvcir.2020.103008
- Cloud segmentation property extraction from total sky image repositories using Python D. Igoe et al. 10.1080/10739149.2019.1603996
- A Novel Parameter Adaptive Dual Channel MSPCNN Based Single Image Dehazing for Intelligent Transportation Systems G. Sahu et al. 10.1109/TITS.2022.3225797
- Retrieval of Atmospheric Profiles in the New York State Mesonet Using One‐Dimensional Variational Algorithm J. Yang & Q. Min 10.1029/2018JD028272
- Real-World Remote Sensing Image Dehazing: Benchmark and Baseline Z. Zhu et al. 10.1109/TGRS.2025.3584234
- CloudRaednet: residual attention-based encoder–decoder network for ground-based cloud images segmentation in nychthemeron C. Shi et al. 10.1080/01431161.2022.2054298
- New color channel driven physical lighting model for low-light image enhancement S. Kucuk et al. 10.1016/j.dsp.2024.104757
- (Retracted) Method of defogging unmanned aerial vehicle images based on intelligent manufacturing P. Wang et al. 10.1117/1.JEI.32.1.011216
- Analyzing of Cloud Macroscopic Characteristics in the Shigatse Area of the Tibetan Plateau Using the Total-Sky Images J. Yang et al. 10.1175/JAMC-D-18-0095.1
15 citations as recorded by crossref.
- Cloud detection method using ground-based sky images based on clear sky library and superpixel local threshold Y. Niu et al. 10.1016/j.renene.2024.120452
- Pixel‐Based Image Processing for CIE Standard Sky Classification through ANN D. Granados-López et al. 10.1155/2021/2636157
- A Cloud Detection Algorithm with Reduction of Sunlight Interference in Ground-Based Sky Images X. Li et al. 10.3390/atmos10110640
- Retrieval of Oceanic Total Precipitable Water Vapor and Cloud Liquid Water from Fengyun-3D Microwave Sounding Instruments Y. Han et al. 10.1007/s13351-021-0084-4
- Characteristics of Surface Solar Radiation under Different Air Pollution Conditions over Nanjing, China: Observation and Simulation H. Luo et al. 10.1007/s00376-019-9010-4
- Diurnal and nocturnal cloud segmentation of all-sky imager (ASI) images using enhancement fully convolutional networks C. Shi et al. 10.5194/amt-12-4713-2019
- Single image dehazing using a new color channel G. Sahu et al. 10.1016/j.jvcir.2020.103008
- Cloud segmentation property extraction from total sky image repositories using Python D. Igoe et al. 10.1080/10739149.2019.1603996
- A Novel Parameter Adaptive Dual Channel MSPCNN Based Single Image Dehazing for Intelligent Transportation Systems G. Sahu et al. 10.1109/TITS.2022.3225797
- Retrieval of Atmospheric Profiles in the New York State Mesonet Using One‐Dimensional Variational Algorithm J. Yang & Q. Min 10.1029/2018JD028272
- Real-World Remote Sensing Image Dehazing: Benchmark and Baseline Z. Zhu et al. 10.1109/TGRS.2025.3584234
- CloudRaednet: residual attention-based encoder–decoder network for ground-based cloud images segmentation in nychthemeron C. Shi et al. 10.1080/01431161.2022.2054298
- New color channel driven physical lighting model for low-light image enhancement S. Kucuk et al. 10.1016/j.dsp.2024.104757
- (Retracted) Method of defogging unmanned aerial vehicle images based on intelligent manufacturing P. Wang et al. 10.1117/1.JEI.32.1.011216
- Analyzing of Cloud Macroscopic Characteristics in the Shigatse Area of the Tibetan Plateau Using the Total-Sky Images J. Yang et al. 10.1175/JAMC-D-18-0095.1
Latest update: 15 Aug 2025
Short summary
A big challenge for accurate cloud detection is the inhomogeneous brightness distribution of sky background, which mainly caused by the difference in atmospheric scattering angles. In this manuscript, we report a new RGB channel operation aiming to remove this inhomogeneous sky background in the total sky images, and then a cloud detection algorithm based on this new channel is proposed which combined the merits of the threshold and differencing methods.
A big challenge for accurate cloud detection is the inhomogeneous brightness distribution of sky...
