Accurate SAR Aircraft Detection Algorithm Based on Feature Enhancement

Aircraft detection in synthetic aperture radar (SAR) images is of much significance because of its all-weather, all-day, and strong penetrating characteristics. However, existing algorithms exhibit inadequate capacity for feature extraction due to imaging discontinuities and background interference of SAR images. To overcome these task-specific issues, we proposed a feature enhancement-based SAR aircraft detection algorithm. In detail, we employed Adaptive Contrast Enhancement (ACE) in the preprocessing stage to reduce noises, and then we embed Scatter Point Focused Module (SPFM) into network to enhance the feature extraction of aircraft scattering points. Furthermore, we devised Background Interference Suppression Module (BISM) to accentuate salient points and suppress non-essential pixels. Experimental results on the GaoFen-3 SAR aircraft dataset demonstrate the effectiveness of the proposed feature enhancement-based method.