JERAJournal of Electronic Research and Application2208-35022208-3510Bio-Byword Scientific Publishing Pty. Ltd.10.26689/jera.v9i6.12055ArticleAW-HRNet: A Lightweight High-Resolution Crack Segmentation Network Integrating Spatial Robustness and Frequency-Domain Enhancementhttps://artdesignp.com/journal/JERA/9/6/10.26689/jera.v9i6.12055MaDewang,LuTong2025962025-11-03The study presents AW-HRNet, a lightweight high-resolution crack segmentation network that couples Adaptive residual enhancement (AREM) in the spatial domain with Wavelet-based decomposition–reconstruction (WDRM) in the frequency domain. AREM introduces a learnable channel-wise scaling after standard 3 × 3 convolution and merges it through a residual path to stabilize crack-sensitive responses while suppressing noise. WDRM performs DWT to decouple LL/LH/HL/HH sub-bands, conducts lightweight cross-band fusion, and applies IDWT to restore detail-enhanced features, unifying global topology and boundary sharpness without deformable offsets. Integrated into a high-resolution backbone with auxiliary deep supervision, AW-HRNet attains 79.07% mIoU on CrackSeg9k with only 1.24M parameters and 0.73 GFLOPs, offering an excellent accuracy–efficiency trade-off and strong robustness for real-world deployment.

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