Abstract
Storm detection algorithm is a key element of the severe weather surveillance service based on radar image data. 3-D clustering technique is the fundamental part of storm detection. During the clustering process, the connection area between adjacent storms may cause the existing algorithms to identify them as one storm wrongly. Isolating storms from a cluster of storms is another difficulty. To overcome these difficulties, this paper introduces a novel approach which combines the strengths of erosion and dilation in a special way. First, the erosion operation is used to solve the problem of false merger. Then the dilation operation is performed when using gradually increased threshold to detect storms. This keeps the internal structure information of sub-storms well when isolating storms from a cluster of storms. The results of the experiment show that this method can correctly recognize adjacent storms. And when isolating storms from a cluster of storms, this method can also keep the internal structure of sub-storms which will benefit the following tracking task.
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Han, L., Wang, HQ., Zhao, LF., Fu, SX. (2007). A Novel Approach for Storm Detection Based on 3-D Radar Image Data. In: Bebis, G., et al. Advances in Visual Computing. ISVC 2007. Lecture Notes in Computer Science, vol 4842. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-76856-2_41
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DOI: https://doi.org/10.1007/978-3-540-76856-2_41
Publisher Name: Springer, Berlin, Heidelberg
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