An automated cloud detection method based on the green channel of total-sky visible images
Obtaining an accurate cloud-cover state is a challenging task. In the past, traditional two-dimensional red-to-blue band methods have been widely used for cloud detection in total-sky images. By analyzing the imaging principle of cameras, the green channel has been selected to replace the 2-D red-to...
| Main Authors: | , , , , , , , |
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| Format: | Article |
| Language: | English |
| Published: |
Copernicus Publications
2015-11-01
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| Series: | Atmospheric Measurement Techniques |
| Online Access: | http://www.atmos-meas-tech.net/8/4671/2015/amt-8-4671-2015.pdf |
| _version_ | 1811331984727736320 |
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| author | J. Yang Q. Min W. Lu W. Yao Y. Ma J. Du T. Lu G. Liu |
| author_facet | J. Yang Q. Min W. Lu W. Yao Y. Ma J. Du T. Lu G. Liu |
| author_sort | J. Yang |
| collection | DOAJ |
| description | Obtaining an accurate cloud-cover state is a challenging task. In the past,
traditional two-dimensional red-to-blue band methods have been widely used
for cloud detection in total-sky images. By analyzing the imaging principle
of cameras, the green channel has been selected to replace the 2-D red-to-blue
band for detecting cloud pixels from partly cloudy total-sky images in this
study. The brightness distribution in a total-sky image is usually
nonuniform, because of forward scattering and Mie scattering of aerosols,
which results in increased detection errors in the circumsolar and
near-horizon regions. This paper proposes an automatic cloud detection
algorithm, "green channel background subtraction adaptive threshold"
(GBSAT), which incorporates channel selection, background simulation,
computation of solar mask and cloud mask, subtraction, an adaptive threshold,
and binarization. Five experimental cases show that the GBSAT algorithm
produces more accurate retrieval results for all these test total-sky
images. |
| first_indexed | 2024-04-13T16:29:06Z |
| format | Article |
| id | doaj.art-dd6c96e1659b430ead4ef47c9fbb3095 |
| institution | Directory Open Access Journal |
| issn | 1867-1381 1867-8548 |
| language | English |
| last_indexed | 2024-04-13T16:29:06Z |
| publishDate | 2015-11-01 |
| publisher | Copernicus Publications |
| record_format | Article |
| series | Atmospheric Measurement Techniques |
| spelling | doaj.art-dd6c96e1659b430ead4ef47c9fbb30952022-12-22T02:39:39ZengCopernicus PublicationsAtmospheric Measurement Techniques1867-13811867-85482015-11-018114671467910.5194/amt-8-4671-2015An automated cloud detection method based on the green channel of total-sky visible imagesJ. Yang0Q. Min1W. Lu2W. Yao3Y. Ma4J. Du5T. Lu6G. Liu7State Key Laboratory of Severe Weather, Chinese Academy of Meteorological Sciences, Beijing 100081, ChinaAtmospheric Sciences Research Center, State University of New York, Albany, NY 12203, USAState Key Laboratory of Severe Weather, Chinese Academy of Meteorological Sciences, Beijing 100081, ChinaState Key Laboratory of Severe Weather, Chinese Academy of Meteorological Sciences, Beijing 100081, ChinaState Key Laboratory of Severe Weather, Chinese Academy of Meteorological Sciences, Beijing 100081, ChinaSchool of Remote Sensing and Information Engineering, Wuhan University, Wuhan 430079, ChinaState Key Laboratory of Severe Weather, Chinese Academy of Meteorological Sciences, Beijing 100081, ChinaSmart Grid Operation Research Center, China Electric Power Research Institute, Beijing 100192, ChinaObtaining an accurate cloud-cover state is a challenging task. In the past, traditional two-dimensional red-to-blue band methods have been widely used for cloud detection in total-sky images. By analyzing the imaging principle of cameras, the green channel has been selected to replace the 2-D red-to-blue band for detecting cloud pixels from partly cloudy total-sky images in this study. The brightness distribution in a total-sky image is usually nonuniform, because of forward scattering and Mie scattering of aerosols, which results in increased detection errors in the circumsolar and near-horizon regions. This paper proposes an automatic cloud detection algorithm, "green channel background subtraction adaptive threshold" (GBSAT), which incorporates channel selection, background simulation, computation of solar mask and cloud mask, subtraction, an adaptive threshold, and binarization. Five experimental cases show that the GBSAT algorithm produces more accurate retrieval results for all these test total-sky images.http://www.atmos-meas-tech.net/8/4671/2015/amt-8-4671-2015.pdf |
| spellingShingle | J. Yang Q. Min W. Lu W. Yao Y. Ma J. Du T. Lu G. Liu An automated cloud detection method based on the green channel of total-sky visible images Atmospheric Measurement Techniques |
| title | An automated cloud detection method based on the green channel of total-sky visible images |
| title_full | An automated cloud detection method based on the green channel of total-sky visible images |
| title_fullStr | An automated cloud detection method based on the green channel of total-sky visible images |
| title_full_unstemmed | An automated cloud detection method based on the green channel of total-sky visible images |
| title_short | An automated cloud detection method based on the green channel of total-sky visible images |
| title_sort | automated cloud detection method based on the green channel of total sky visible images |
| url | http://www.atmos-meas-tech.net/8/4671/2015/amt-8-4671-2015.pdf |
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