基于非平稳性和极化相干系数比的PolSAR图像建筑物检测

为了提高全极化合成孔径雷达(PolSAR)图像中城区建筑物的检测精度，该文提出一种基于人造目标散射非平稳性和极化相干系数比的建筑物检测新方法。该方法首先对PolSAR图像进行滤波和方位向时频分解，得到多个子孔径图像，然后结合方位向非平稳性检测和极化相干系数比来判断某个像素是否为建筑物。该文通过引入一种新的极化相干系数比从而使获取的建筑物检测结果优于传统非平稳性检测方法，能够有效去除具有布拉格散射的自然地物虚警从而提高检测精度。星载和机载PolSAR数据实验结果验证了该方法的有效性。

Built-up Area Detection from PolSAR Images Based on Nonstationarity and Polarization Coherency Coefficient Ratio

To improve the detection accuracy of urban built-up areas from Polarimetric Synthetic Aperture Radar (PolSAR) images, this paper proposes a new built-up area detection method based on nonstationarity and polarization coherency coefficient ratio. Firstly, the PolSAR image is filtered and decomposed into several sub-aperture images along the azimuth direction. Then nonstationarity detection and polarization coherency coefficient ratio are combined to determine the class label of pixels. On the basis of the traditional nonstationarity detection method, this paper introduces a new polarization coherency coefficient ratio to remove the false alarms of natural areas and to improve the overall detection accuracy. Experimental results using spaceborne and airborne PolSAR data demonstrate the effectiveness of the proposed method.