GPR Bscan Imaging Enhancement Method for Rebar Occlusion

When using ground penetrating radar (GPR) to detect targets below shallow rebar mesh in reinforced concrete structures, the strong scattering characteristics of rebar mesh causes distortion and interference of targets echoes and leads to imaging artifacts and degradation. This letter proposes a coarse-scale and fine-scale dual-branch imaging enhancement network (CFD-IENet) to achieve target imaging under rebar mesh in reinforced concrete by combining Bscan echo data enhancement with BP imaging result enhancement. First, a residual U network (Res-U) suppresses complex background clutter in Bscan data to improve the signal-to-noise ratio. Then, a coarse-scale and fine-scale dual-branch network is constructed to enhance both Bscan and BP imaging. In the Bscan enhancement stage, strong and weak signals are trained separately, aiming for surface rebar echo interference in reconstructing weak target signals beneath the rebar mesh. In the BP imaging enhancement stage, artifacts and multipath ghosts are suppressed to enhance occluded target imaging. A bilinear fusion module (BFM) is designed to facilitate global feature interaction, promoting the fusion of Bscan and BP imaging features across scales, thereby improving reconstruction and enhancement accuracy. Experimental results on cracks occluded by rebar mesh demonstrate the method’s effectiveness, showing a 4.73dB improvement in PSNR and a 0.16 improvement in SSIM compared to the RNMF+BP+Unet enhancement method.