Abstract: Aiming at overcoming the disadvantages of the limitation of class number and misclassification while classifying terrain and land directly by using four components decomposed by Yamaguchi target decomposition method from PolSAR images，a novel unsupervised classification algorithm for full polarimetric SAR images based on four-components scattering model and combined FCM theory is proposed and is applied to deal with L-band PiSAR image.This algorithm uses the four components as input features of FCM cluster.The experimental result demonstrates the accuracy and effectiveness of this algorithm.

摘要： 针对利用Yamaguchi分解模型的四个散射分量直接进行类别归属判断精度不高并且所分类别有限的问题，结合模糊C均值的理论，提出了一种基于Yamaguchi分解模型的全极化SAR分类算法，把四个散射分量组成一组归一化的特征矢量，进行FCM聚类分析。并且用日本机载L波段PiSAR数据验证了该算法具有较高的分类精度和较好的视觉效果。