Articles | Volume 10, issue 3
https://doi.org/10.5194/amt-10-1191-2017
https://doi.org/10.5194/amt-10-1191-2017
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, Qilong Min, Weitao Lu, Ying Ma, Wen Yao, and Tianshu Lu

Abstract. The inhomogeneous sky background presents a great challenge for accurate cloud recognition from the total-sky images. A channel operation was introduced in this study to produce a new composite channel in which the difference of atmospheric scattering has been removed and a homogeneous sky background can be obtained. Following this, a new cloud detection algorithm was proposed that combined the merits of the differencing and threshold methods, named differencing and threshold combination algorithm (DTCA). Firstly, the channel operation was applied to transform 3-D RGB image to the new channel, then the circumsolar saturated pixels and its circularity were used to judge whether the sun is visible or not in the image. When the sun is obscured, a single threshold can be used to identify cloud pixels. If the sun is visible in the image, the true clear-sky background differencing algorithm is adopted to detect clouds. The qualitative assessment for eight different total-sky images shows the DTCA algorithm obtained satisfactory cloud identification effectiveness for thin clouds and in the circumsolar and near-horizon regions. Quantitative evaluation also shows that the DTCA algorithm achieved the highest cloud recognition precision for five different types of clouds and performed well under both visible sun and blocked sun conditions.

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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.