A Physics-Guided Adaptive Bayesian Optimization Framework for Training-Free Underwater Image Enhancement

Reliable underwater visual perception plays a critical role in marine exploration, autonomous underwater vehicles, and subsea inspection. Nevertheless, underwater images are frequently degraded by severe color distortion, contrast reduction, and structural information loss due to wavelength-dependent light attenuation and scattering. Existing enhancement approaches either depend on fixed physical assumptions or require data-driven models, which often limits their adaptability across diverse underwater environments. To address these challenges, this paper presents a Physics-Guided Adaptive Bayesian Optimization (PG-ABO) framework for training-free underwater image enhancement. By combining physical degradation priors with image-specific parameter optimization, the proposed approach enables enhancement strategies to adapt dynamically to varying underwater conditions without relying on paired training data. The proposed framework incorporates an improved underwater dark channel prior with structure-aware transmission refinement to establish a physically consistent initial representation. Subsequently, a dual-path optimization strategy is constructed to generate complementary enhancement candidates by separately targeting color fidelity and structural perception. Bayesian optimization is employed to adaptively search enhancement parameters under the guidance of UCIQE and UIQM objectives. Furthermore, a robust multi-scale fusion strategy with anti-hotspot weight regulation is introduced, while a metric-aware refinement module is applied to enhance perceptual consistency and reduce enhancement artifacts. Experiments conducted on three underwater image datasets, including U45, UIEB, and LSUI, verify the effectiveness and robustness of the proposed framework across diverse underwater conditions. Consequently, the proposed method provides an adaptive, training-free, and physically motivated solution for underwater image enhancement under complex degradation conditions.