Spatio-Temporal Detection of Cumulonimbus Clouds in Infrared Satellite Images

Ron Dorfman, Etai Wagner, Almog Lahav, A. Amar, R. Talmon, Yaron Halle
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Abstract

In this paper, we address the problem of Cumulonimbus (Cb) cloud detection from Infrared (IR) satellite images. The detection of such storm clouds is of high importance since they pose extreme danger to aviation. We present a joint spatio-temporal detection method that exploits the distinct spatial characteristics of Cb clouds as well as their prototypical evolution over time. The presented method is unsupervised and does not require labeled data or predefined spatial handcrafted features, such as particular shapes, temperatures, textures, and gradients. We demonstrate the performance of the proposed method on several sequences of IR satellite images taken from the middle east region.
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红外卫星图像中积雨云的时空探测
本文研究了利用红外卫星图像检测积雨云的问题。探测这种风暴云是非常重要的,因为它们对航空构成了极大的危险。我们提出了一种联合时空检测方法,该方法利用了Cb云的独特空间特征及其随时间的典型演化。所提出的方法是无监督的,不需要标记数据或预定义的空间手工特征,如特定的形状、温度、纹理和梯度。我们对中东地区的红外卫星图像序列进行了验证。
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