A Modified Framework for Ship Detection from Compact Polarization SAR Image

In recent years, the compact polarimetric SAR (CP SAR) imaging mode has received much attention because of its advantages in swath width compared to the quad-polarization mode and in information of scattering targets compared to the linear dual-polarization mode, respectively. For object detection (e.g., ship, sea ice, and drilling platform) in maritime monitoring which has been widely discussed, it is still a challenge to eliminate the false alarms caused by ocean clutter. Accordingly, a modified feature-based framework for ship detection using CP SAR data was proposed in this paper. In particular, a Guard-filter was used after feature extraction to reduce the effect of ocean clutter. Several simulated CP SAR imageries based on Gaofen-3 quad-polarization SAR image were selected for further investigations on ship detection. A SVM classifier was included in the framework to do a pixel-wise classification. The result shows that the proposed method has a better performance compared to traditional methods (e.g., constant false alarm rate and polarimetric whitening filter) and the feature-based method without filtering. Overall false alarm rates are decreased by 35% with the proposed method.