中文摘要：

本文提出了一种基于散射模型的多时相极化SAR数据斑点噪声滤波算法，该方法是利用多时相极化SAR数据，在保持像元主散射特性基础上实现斑点噪声抑制。其基本原理是对多时相极化SAR数据的主辅影像进行分类，并通过统计主辅影像中待滤波像元邻域窗口内类别分布情况自适应地选取参与滤波的像素进行滤波。实测数据的实验结果表明，该方法既能够有效地抑制斑点噪声，又能够良好地保持地物散射特性和边缘纹理特征。

英文摘要：

The speckle noise in SAR image seriously affects the SAR image interpretation and application. To solve the problem, the paper proposed a speckle filtering method named scattering-model-based speckle filtering for multi-temporal polarimetric SAR （PolSAR） data. It can reduce the speckle effectively and preserve the dominant scattering mechanism of targets by using the multi-temporal polarimetric SAR data. The basic idea is to compare the category of central pixel between the master classification map and the slave classification map within a sliding window. The method first applied the unsupervised classification method to classify the master and slave images. Then it selected the pixels involved in the filtering process adaptively based on the statistics of the category distribution of the pixels within the neighborhood window in the master and slave classification maps. The experimental results proved the effectiveness of the algorithm in the speckle reduction.