红外技术Issue(3)：150-154,5.
基于改进FCM算法的卫星云图聚类方法研究
Satellite Image Clustering Research Based on Improved FCM Algorithm
摘要
Abstract
Nephograms can be used to analyze the distribution of the cloud system in a large area, and to study the evolvement rules of weather system. We can analyze the nephograms without the interference of terrestrial and marine information by extract the clouds content from the nephograms. So fuzzy C-means(FCM) algorithm is used for satellite image clustering. The method is easy to understand, but it always converges to the local infinitesimal values. So PSO was introduced to FCM algorithm, which can find a globally optimal fuzzy segmentation so as to avoid the sensitivities of basic FCM algorithm to initial values. In order to improve the speed of the algorithm, the shadow sets algorithm was combined with FCM, which can remove boundary values and abnormal values. The results show that the clustering effect of the newly-proposed algorithm is better than the one of the basic FCM.关键词
模糊C均值算法/阴影集/粒子群算法/卫星云图聚类Key words
fuzzy C-means algorithm/shadow sets/PSO/satellite cloud image clustering分类
信息技术与安全科学引用本文复制引用
李秀馨,王敬东,徐烨晔,温家旺..基于改进FCM算法的卫星云图聚类方法研究[J].红外技术,2013,(3):150-154,5.基金项目
国家自然科学基金(编号:61074161) （编号:61074161）
