GPU-accelerated main road extraction in Polarimetric SAR images based on MRF

Road extraction in SAR (Synthetic Aperture Radar) images is a difficult task because of speckle noise and various interferences. PolSAR (Polarimetric SAR) measures road's reflectivity in four polarizations and provides more information of road, which potentially indicates higher extraction performance than that in single-polarization SAR cases. However, the implementation of the traditional MRF (Markov Random Field) based road extraction method needs excessive computation operations, which is relatively time consuming and difficult for application. This letter presents a GPU-accelerated road extraction method in PolSAR images with five stages. Firstly, the total power is calculated to form the span image. Then, pixels of the similar scattering property are included in the refined Lee filtering process. Thirdly, the edges are detected by the bi-windows edge detection algorithm. Fourthly, line pre-processing and graph construction are done to decrease the false line elements and form the line graph. Finally, the MRF is used to extract road line elements. The experiments have proved that such a GPU-accelerated approach can improve the computing efficiency, and the effectiveness is demonstrated by using the airborne PolSAR image acquired over the Oberpfaffenhofen area in Germany.