A total sky cloud detection method using real clear sky background

The brightness distribution of sky background is usually non-uniform, which creates many problems for traditional cloud detection methods, including the failure of thin cloud detection in total sky images and significantly reducing retrieval accuracy in the circumsolar and near-horizon regions. This...
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Autor*in:	J. Yang [verfasserIn] Q. Min [verfasserIn] W. Lu [verfasserIn] Y. Ma [verfasserIn] W. Yao [verfasserIn] T. Lu [verfasserIn] J. Du [verfasserIn] G. Liu [verfasserIn]

Format:	E-Artikel
Sprache:	Englisch

Erschienen:	2016

Übergeordnetes Werk:	In: Atmospheric Measurement Techniques - Copernicus Publications, 2009, 9(2016), 2, Seite 587-597
Übergeordnetes Werk:	volume:9 ; year:2016 ; number:2 ; pages:587-597

Links:	Link aufrufen Link aufrufen Link aufrufen Journal toc Journal toc

DOI / URN:	10.5194/amt-9-587-2016

Katalog-ID:	DOAJ049984608

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spelling	10.5194/amt-9-587-2016 doi (DE-627)DOAJ049984608 (DE-599)DOAJ02e0ed9abe2c4a0a9c30541dffcc30a4 DE-627 ger DE-627 rakwb eng TA170-171 TA715-787 J. Yang verfasserin aut A total sky cloud detection method using real clear sky background 2016 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier The brightness distribution of sky background is usually non-uniform, which creates many problems for traditional cloud detection methods, including the failure of thin cloud detection in total sky images and significantly reducing retrieval accuracy in the circumsolar and near-horizon regions. This paper describes the development of a new cloud detection algorithm, named "clear sky background differencing (CSBD)", which is accomplished by differencing the original image and the corresponding clear sky background image using the images' green channel. First, a library of clear sky background images with a variety of solar elevation angles needs to be developed. The image rotation and image brightness adjustment algorithms are applied to ensure the two images being differenced have the same solar position and similar brightness distribution. Sensitivity tests show that the cloud detection results are satisfactory when the two images have the same solar positions. Several experimental cases show that the CSBD algorithm obtains good cloud recognition results visually, especially for thin clouds. Environmental engineering Earthwork. Foundations Q. Min verfasserin aut W. Lu verfasserin aut Y. Ma verfasserin aut W. Yao verfasserin aut T. Lu verfasserin aut J. Du verfasserin aut G. Liu verfasserin aut In Atmospheric Measurement Techniques Copernicus Publications, 2009 9(2016), 2, Seite 587-597 (DE-627)605214441 (DE-600)2505596-3 18678548 nnns volume:9 year:2016 number:2 pages:587-597 https://doi.org/10.5194/amt-9-587-2016 kostenfrei https://doaj.org/article/02e0ed9abe2c4a0a9c30541dffcc30a4 kostenfrei http://www.atmos-meas-tech.net/9/587/2016/amt-9-587-2016.pdf kostenfrei https://doaj.org/toc/1867-1381 Journal toc kostenfrei https://doaj.org/toc/1867-8548 Journal toc kostenfrei GBV_USEFLAG_A SYSFLAG_A GBV_DOAJ SSG-OLC-PHA GBV_ILN_11 GBV_ILN_20 GBV_ILN_22 GBV_ILN_23 GBV_ILN_24 GBV_ILN_31 GBV_ILN_39 GBV_ILN_40 GBV_ILN_60 GBV_ILN_62 GBV_ILN_63 GBV_ILN_65 GBV_ILN_69 GBV_ILN_70 GBV_ILN_73 GBV_ILN_95 GBV_ILN_105 GBV_ILN_110 GBV_ILN_151 GBV_ILN_161 GBV_ILN_170 GBV_ILN_206 GBV_ILN_213 GBV_ILN_230 GBV_ILN_267 GBV_ILN_285 GBV_ILN_293 GBV_ILN_370 GBV_ILN_602 GBV_ILN_2003 GBV_ILN_2005 GBV_ILN_2009 GBV_ILN_2011 GBV_ILN_2014 GBV_ILN_2055 GBV_ILN_2111 GBV_ILN_4012 GBV_ILN_4037 GBV_ILN_4112 GBV_ILN_4125 GBV_ILN_4126 GBV_ILN_4249 GBV_ILN_4305 GBV_ILN_4306 GBV_ILN_4307 GBV_ILN_4313 GBV_ILN_4322 GBV_ILN_4323 GBV_ILN_4324 GBV_ILN_4325 GBV_ILN_4338 GBV_ILN_4367 GBV_ILN_4700 AR 9 2016 2 587-597
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allfieldsSound	10.5194/amt-9-587-2016 doi (DE-627)DOAJ049984608 (DE-599)DOAJ02e0ed9abe2c4a0a9c30541dffcc30a4 DE-627 ger DE-627 rakwb eng TA170-171 TA715-787 J. Yang verfasserin aut A total sky cloud detection method using real clear sky background 2016 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier The brightness distribution of sky background is usually non-uniform, which creates many problems for traditional cloud detection methods, including the failure of thin cloud detection in total sky images and significantly reducing retrieval accuracy in the circumsolar and near-horizon regions. This paper describes the development of a new cloud detection algorithm, named "clear sky background differencing (CSBD)", which is accomplished by differencing the original image and the corresponding clear sky background image using the images' green channel. First, a library of clear sky background images with a variety of solar elevation angles needs to be developed. The image rotation and image brightness adjustment algorithms are applied to ensure the two images being differenced have the same solar position and similar brightness distribution. Sensitivity tests show that the cloud detection results are satisfactory when the two images have the same solar positions. Several experimental cases show that the CSBD algorithm obtains good cloud recognition results visually, especially for thin clouds. Environmental engineering Earthwork. Foundations Q. Min verfasserin aut W. Lu verfasserin aut Y. Ma verfasserin aut W. Yao verfasserin aut T. Lu verfasserin aut J. Du verfasserin aut G. Liu verfasserin aut In Atmospheric Measurement Techniques Copernicus Publications, 2009 9(2016), 2, Seite 587-597 (DE-627)605214441 (DE-600)2505596-3 18678548 nnns volume:9 year:2016 number:2 pages:587-597 https://doi.org/10.5194/amt-9-587-2016 kostenfrei https://doaj.org/article/02e0ed9abe2c4a0a9c30541dffcc30a4 kostenfrei http://www.atmos-meas-tech.net/9/587/2016/amt-9-587-2016.pdf kostenfrei https://doaj.org/toc/1867-1381 Journal toc kostenfrei https://doaj.org/toc/1867-8548 Journal toc kostenfrei GBV_USEFLAG_A SYSFLAG_A GBV_DOAJ SSG-OLC-PHA GBV_ILN_11 GBV_ILN_20 GBV_ILN_22 GBV_ILN_23 GBV_ILN_24 GBV_ILN_31 GBV_ILN_39 GBV_ILN_40 GBV_ILN_60 GBV_ILN_62 GBV_ILN_63 GBV_ILN_65 GBV_ILN_69 GBV_ILN_70 GBV_ILN_73 GBV_ILN_95 GBV_ILN_105 GBV_ILN_110 GBV_ILN_151 GBV_ILN_161 GBV_ILN_170 GBV_ILN_206 GBV_ILN_213 GBV_ILN_230 GBV_ILN_267 GBV_ILN_285 GBV_ILN_293 GBV_ILN_370 GBV_ILN_602 GBV_ILN_2003 GBV_ILN_2005 GBV_ILN_2009 GBV_ILN_2011 GBV_ILN_2014 GBV_ILN_2055 GBV_ILN_2111 GBV_ILN_4012 GBV_ILN_4037 GBV_ILN_4112 GBV_ILN_4125 GBV_ILN_4126 GBV_ILN_4249 GBV_ILN_4305 GBV_ILN_4306 GBV_ILN_4307 GBV_ILN_4313 GBV_ILN_4322 GBV_ILN_4323 GBV_ILN_4324 GBV_ILN_4325 GBV_ILN_4338 GBV_ILN_4367 GBV_ILN_4700 AR 9 2016 2 587-597
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topic_title	TA170-171 TA715-787 A total sky cloud detection method using real clear sky background
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title	A total sky cloud detection method using real clear sky background
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title_sort	total sky cloud detection method using real clear sky background
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title_auth	A total sky cloud detection method using real clear sky background
abstract	The brightness distribution of sky background is usually non-uniform, which creates many problems for traditional cloud detection methods, including the failure of thin cloud detection in total sky images and significantly reducing retrieval accuracy in the circumsolar and near-horizon regions. This paper describes the development of a new cloud detection algorithm, named "clear sky background differencing (CSBD)", which is accomplished by differencing the original image and the corresponding clear sky background image using the images' green channel. First, a library of clear sky background images with a variety of solar elevation angles needs to be developed. The image rotation and image brightness adjustment algorithms are applied to ensure the two images being differenced have the same solar position and similar brightness distribution. Sensitivity tests show that the cloud detection results are satisfactory when the two images have the same solar positions. Several experimental cases show that the CSBD algorithm obtains good cloud recognition results visually, especially for thin clouds.
abstractGer	The brightness distribution of sky background is usually non-uniform, which creates many problems for traditional cloud detection methods, including the failure of thin cloud detection in total sky images and significantly reducing retrieval accuracy in the circumsolar and near-horizon regions. This paper describes the development of a new cloud detection algorithm, named "clear sky background differencing (CSBD)", which is accomplished by differencing the original image and the corresponding clear sky background image using the images' green channel. First, a library of clear sky background images with a variety of solar elevation angles needs to be developed. The image rotation and image brightness adjustment algorithms are applied to ensure the two images being differenced have the same solar position and similar brightness distribution. Sensitivity tests show that the cloud detection results are satisfactory when the two images have the same solar positions. Several experimental cases show that the CSBD algorithm obtains good cloud recognition results visually, especially for thin clouds.
abstract_unstemmed	The brightness distribution of sky background is usually non-uniform, which creates many problems for traditional cloud detection methods, including the failure of thin cloud detection in total sky images and significantly reducing retrieval accuracy in the circumsolar and near-horizon regions. This paper describes the development of a new cloud detection algorithm, named "clear sky background differencing (CSBD)", which is accomplished by differencing the original image and the corresponding clear sky background image using the images' green channel. First, a library of clear sky background images with a variety of solar elevation angles needs to be developed. The image rotation and image brightness adjustment algorithms are applied to ensure the two images being differenced have the same solar position and similar brightness distribution. Sensitivity tests show that the cloud detection results are satisfactory when the two images have the same solar positions. Several experimental cases show that the CSBD algorithm obtains good cloud recognition results visually, especially for thin clouds.
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title_short	A total sky cloud detection method using real clear sky background
url	https://doi.org/10.5194/amt-9-587-2016 https://doaj.org/article/02e0ed9abe2c4a0a9c30541dffcc30a4 http://www.atmos-meas-tech.net/9/587/2016/amt-9-587-2016.pdf https://doaj.org/toc/1867-1381 https://doaj.org/toc/1867-8548
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