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

机译:消除大气散射差异的RGB通道操作及其在全天云探测中的应用

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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 qdifferencing and threshold combination algorithm/q (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.
机译:不均匀的天空背景对从全天空图像中准确识别云提出了巨大的挑战。在这项研究中引入了一个通道操作,以产生一个新的复合通道,其中消除了大气散射的差异,可以获得均匀的天空背景。在此基础上,提出了一种结合差分和阈值方法优点的新型云检测算法,称为差分与阈值组合算法。首先,应用通道运算将3-D RGB图像转换为新通道,然后使用绕线饱和像素及其圆度来判断图像中是否可见太阳。当太阳被遮挡时,可以使用单个阈值来识别云像素。如果图像中可见太阳,则采用真正的晴空背景差分算法来检测云。对八幅不同的全天图像的定性评估表明,DTCA算法对于薄云以及在周边和近地平线地区获得了令人满意的云识别效果。定量评估还表明,DTCA算法针对五种不同类型的云实现了最高的云识别精度,并且在可见太阳和被遮挡的太阳条件下均表现良好。

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