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The inhomogeneous sky background presents a greatchallenge for accurate cloud recognition from the total-sky images. Achannel operation was introduced in this study to produce a new compositechannel in which the difference of atmospheric scattering has been removedand a homogeneous sky background can be obtained. Following this, a newcloud detection algorithm was proposed that combined the merits of thedifferencing and threshold methods, named <q>differencing and thresholdcombination algorithm</q> (DTCA). Firstly, the channel operation was appliedto transform 3-D RGB image to the new channel, then the circumsolarsaturated pixels and its circularity were used to judge whether the sun isvisible or not in the image. When the sun is obscured, a single thresholdcan be used to identify cloud pixels. If the sun is visible in the image,the true clear-sky background differencing algorithm is adopted to detectclouds. The qualitative assessment for eight different total-sky imagesshows the DTCA algorithm obtained satisfactory cloud identificationeffectiveness for thin clouds and in the circumsolar and near-horizonregions. Quantitative evaluation also shows that the DTCA algorithm achieved thehighest cloud recognition precision for five different types of clouds andperformed well under both visible sun and blocked sun conditions

An RGB channel operation for removal of the difference of atmospheric scattering and its application on total sky cloud detection