极化合成孔径雷达（synthetic aperture radar，SAR）图像为雷达图像中的信息处理和获取提供了更为便捷的途径。提出了基于独立分量分析(independent component analysis，ICA)的极化SAR图像相干斑抑制方法。该方法将极化SAR图像斑点噪声的乘积模型，变换为应用ICA的信号加噪模型。并且将HV/VV的比值图像，也作为ICA的输入数据。分别使用几种不同的ICA算法，得到了分别对应于HH、HV和VV极化的3幅降噪图像，并对结果进行了比较分析。实验结果表明，应用ICA算法可以有效地降低极化SAR图像的相干斑噪声，提高图像质量。

The polarimetric SAR(synthetic aperture radar) image provides a very convenient approach for signal processing and acquisition of information from radar image. Based on statistical formulation of polarimetric SAR image, we present a new approach for speckle reduction using ICA (independent component analysis). In addition, we apply some ICA algorithms to real polarimetric SAR images and compare their performences. The comparison reveals characteristic differences between the studied ICA algorithms, complementing the results obtained earlier. The experimental results show that excellent performence can be achieved, the ENL is high and the image speckle noise is reduced effectively.