| 引用本文: | 来旭,李国辉,张军.基于半监督FCM聚类算法的卫星云图分类.[J].国防科技大学学报,2008,30(6):73-77.[点击复制] |
| LAI Xu,LI Guohui,ZHANG Jun.Satellite Cloud Images Classification Based on Semi-supervised FCM Method[J].Journal of National University of Defense Technology,2008,30(6):73-77[点击复制] |
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| 基于半监督FCM聚类算法的卫星云图分类 |
| 来旭, 李国辉, 张军 |
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(国防科技大学 信息系统与管理学院，湖南 长沙 410073)
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| 摘要: |
| 针对卫星云图的特点在分类特征集中采用了一种新的特征——差异化特征，该特征反映了云图的内部结构特点，并且具有良好的鲁棒性，能有效地避免云团位置变化对特征的影响。将半监督思想引入到模糊C均值聚类方法(FCM)，克服了单纯的FCM方法未考虑领域知识导致的聚类结果的盲目性。半监督FCM方法在聚类过程中加入少量的由领域专家标记的样本，引入专家的领域知识，通过与这些带有类标记的样本进行相似性比较，引导FCM方法的聚类过程。试验结果表明，基于具有差异化特征的云图特征集，半监督FCM方法能有效地提高云图分类的准确率。 |
| 关键词: 差异化特征 半监督FCM 卫星云图分类 |
| DOI： |
| 投稿日期：2008-02-18 |
| 基金项目:国家自然基金资助项目(60473116) |
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| Satellite Cloud Images Classification Based on Semi-supervised FCM Method |
| LAI Xu, LI Guohui, ZHANG Jun |
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(College of Information System and Management, National Univ. of Defense Technology, Changsha 410073，China)
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| Abstract: |
| The paper proposes a new classification feature: DI(Diversity Index), considering the characteristics of satellite cloud image. The DI feature presents the structure of cloud effectively and it has a good robustness. The DI feature avoids the influence exerted by the variety of cloud positions. This paper proposes the semi-supervised FCM (SSFCM) method in the domain of satellite cloud images classification. The SSFCM method overcomes the blindness brought by the FCM method without considering the domain knowledge. The SSFCM method uses a small number of samples labeled by experts to direct the clustering process through comparing with the labeled samples in terms of similarity. These labeled samples represent the domain knowledge. The experiments demonstrate that the SSFCM method improves the accuracy of cloud classification based on the DI feature. |
| Keywords: diversity index (DI) semi-supervised FCM satellite cloud classification |
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