Share Email Print

Proceedings Paper

Remote sensing ocean data analyses using fuzzy C-Means clustering
Author(s): Suqin Xu; Jie Chen
Format Member Price Non-Member Price
PDF $17.00 $21.00

Paper Abstract

With the deep understanding and exploitation of the wide Ocean, There are more and more fine instrument installed or loaded on measuring ships or other marines. The high costs and complexity of corrosion place ever-increasing demands on the analyses of surrounding ocean environment. In this paper, the fuzzy C-Means clustering is used to analyze the surrounding ocean environment with remote sensing data. The studied ocean area is considered as a two dimensional gird or an image, and the fuzzy C-Means clustering technique is used to reveal the underlying relationship of the elements and segment the interrelated ocean in regions with similar spectral properties in the influence of instrument corrosion. The influence of the environment elements in instrument corrosion is studied and a priori spatial information is added to improving the segmentation result. The fitness function containing neighbor information was set up based on the gray information and the neighbor relations between the pixels. By making use of the global searching ability of the predator-prey particle swarm optimization, the optimal cluster center could be obtained by iterative optimization and the segmentation could be accomplished. The calculation results show that the segmentation is accurate and reasonable. This ocean environment analysis fruit has used in real application and has proved to be valuable in ship instrument corrosion monitoring and the guide of other ocean activity.

Paper Details

Date Published: 30 October 2009
PDF: 5 pages
Proc. SPIE 7498, MIPPR 2009: Remote Sensing and GIS Data Processing and Other Applications, 74980S (30 October 2009); doi: 10.1117/12.833199
Show Author Affiliations
Suqin Xu, Navy Submarine Academy (China)
Jie Chen, Navy Submarine Academy (China)
Xi'an Research Institute of Hi-Tech, Hongqing Town (China)

Published in SPIE Proceedings Vol. 7498:
MIPPR 2009: Remote Sensing and GIS Data Processing and Other Applications
Faxiong Zhang; Faxiong Zhang, Editor(s)

© SPIE. Terms of Use
Back to Top
Sign in to read the full article
Create a free SPIE account to get access to
premium articles and original research
Forgot your username?