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

[摘要] Obtaining an accurate cloud-cover state is a challenging task. In the past,traditional two-dimensional red-to-blue band methods have been widely usedfor cloud detection in total-sky images. By analyzing the imaging principleof cameras, the green channel has been selected to replace the 2-D red-to-blueband for detecting cloud pixels from partly cloudy total-sky images in thisstudy. The brightness distribution in a total-sky image is usuallynonuniform, because of forward scattering and Mie scattering of aerosols,which results in increased detection errors in the circumsolar andnear-horizon regions. This paper proposes an automatic cloud detectionalgorithm, "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 algorithmproduces more accurate retrieval results for all these test total-skyimages.

[学科分类] 几何与拓扑