PMF-YOLO: a parameter-efficient multi-scale detector for underwater optical imagery under scattering and nonuniform...

Underwater optical images suffer from absorption, scattering, and nonuniform illumination, causing veiling light, contrast loss, and blur that weaken small-target boundaries. We propose PMF-YOLO, a parameter-efficient multi-scale detector based on YOLOv8, to address cross-scale imbalance in underwater feature pyramids: high-resolution details are attenuated while low-resolution semantics can be biased by haze-like backgrounds. PMF-YOLO integrates PMFFPN with channel control and a small-object head, CCSA for boundary/saliency recalibration, and ODSSBlock for efficient global modeling of spatially correlated degradation fields. On URPC2020 Test-A/Test-B and DUO, PMF-YOLO achieves 78.1%, 72.1%, and 86.3% mAP@0.5, exceeding YOLOv8n by 7.9, 6.1, and 3.2 points, respectively, with substantially fewer parameters than stronger detectors.