Multi-Aspect Feature Enhancement Network for Aircraft Detection in High-Resolution SAR Images
Yu Qiu, Bin Zou, Jiang Qin, Lamei Zhang · 2024
Aircraft detection using Synthetic Aperture Radar (SAR) images plays a crucial role in transportation and military applications. Nevertheless, the unique imaging characteristics of SAR often render aircraft targets as discrete points, and their complex geometric structures vary under different imaging conditions. Moreover, the complex background, especially with strong-scattering elements like buildings, significantly complicates detection. To overcome these challenges, this paper introduces a multi-aspect feature enhancement network called MAFEN for aircraft detection in high-resolution SAR images. MAFEN combines a Multi-scale Feature Enhancement Module (MSFEM) with a Key Structure Enhancement Module (KSEM), thereby enhancing detection accuracy and efficiency. Experimental results on public datasets demonstrate significant improvements in detecting aircraft targets in complex scenes.