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Automatic Cloud Detection for All-Sky Images Using Superpixel Segmentation
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DOI：10.1109/LGRS.2014.2341291.png)
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Abstract
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Cloud detection plays an essential role in meteorological research and has received considerable attention in recent years. However, this issue is particularly challenging due to the diverse characteristics of clouds. In this letter, a novel algorithm based on superpixel segmentation (SPS) is proposed for cloud detection. In our proposed strategy, a series of superpixels could be obtained adaptively by SPS algorithm according to the characteristics of clouds. We first calculate a local threshold for each superpixel and then determine a threshold matrix for the whole image. Finally, cloud can be detected by comparing with the obtained threshold matrix. Experimental results show that our proposed algorithm achieves better performance than the current cloud detection algorithms.
Keywords:
Cloud detection
superpixel segmentation (SPS)
threshold matrix
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