an automated cloud detection method based on the green channel of total-sky visible images

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ID: 211170
2015
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Abstract
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.
Reference Key
yang2015atmospherican Use this key to autocite in the manuscript while using SciMatic Manuscript Manager or Thesis Manager
Authors ;J. Yang;Q. Min;W. Lu;W. Yao;Y. Ma;J. Du;T. Lu;G. Liu
Journal bioorganic & medicinal chemistry
Year 2015
DOI
10.5194/amt-8-4671-2015
URL
http://www.atmos-meas-tech.net/8/4671/2015/amt-8-4671-2015.pdf
Keywords
foundations environmental engineeringearthwork

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