4.5 Article

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

Journal

ATMOSPHERIC MEASUREMENT TECHNIQUES
Volume 8, Issue 11, Pages 4671-4679

Publisher

COPERNICUS GESELLSCHAFT MBH
DOI: 10.5194/amt-8-4671-2015

Keywords

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Funding

  1. National Natural Science Foundation of China [41105121, 41105122]
  2. National Key Scientific Instrument and Equipment Development Projects of China [2012YQ11020504]
  3. Basic Research Fund of Chinese Academy of Meteorological Sciences
  4. Science and Technology Research Foundation of SGCC [DZB17201200260]

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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.

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