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Proceedings Paper

Typhoon cloud system segmentation with multichannel images using vector-valued Chan-Vese model
Author(s): Kun Wei; Yuanxiang Li; Zhongliang Jing; Chunxiang Shi
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Paper Abstract

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.

Paper Details

Date Published: 30 October 2009
PDF: 7 pages
Proc. SPIE 7494, MIPPR 2009: Multispectral Image Acquisition and Processing, 749413 (30 October 2009); doi: 10.1117/12.833129
Show Author Affiliations
Kun Wei, Shanghai Jiaotong Univ. (China)
Yuanxiang Li, Shanghai Jiaotong Univ. (China)
Zhongliang Jing, Shanghai Jiaotong Univ. (China)
Chunxiang Shi, National Satellite Meteorological Ctr. (China)

Published in SPIE Proceedings Vol. 7494:
MIPPR 2009: Multispectral Image Acquisition and Processing
Faxiong Zhang; Faxiong Zhang, Editor(s)

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