Cloud segmentation is an important step and a very difficult problem in typhoon image processing. There are many
works on cloud image segmentation, but few are carried out on typhoon primary cloud system (galaxy) segmentation.
Typhoon satellite images are always multiple channels whose properties are very different, so that the appearances of these
channels are different as well. In order to segment out primary cloud systems accurately, multiple channel images are
employed in this paper. The image data is from MERSI (short for MEdium Resolution Spectral Imager) of Chinese FY-
3A meteorological satellite launched on March, 2008. The scalar multiphase Chan-Vese (CV) model is extended for the
vector-valued images, so as to partition out typhoon cloud systems. The experiment results show that the multi-channel
segmentation is more accurate, more complete and more effective than that of usually using only one image, with multiple
channel images being treated as a vector one input into the CV model. The multi-channel segmentation integrates the
distribution information of cloud systems in all channels, so information fusion of multiple channels are realized when
segmenting.
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