Low-Rank Decomposition and Polarization-Driven Transmittance Synergy for Underwater Descattering With Cross-Domain Generalization

To address the challenge of image degradation caused by light scattering in turbid underwater environments, this study proposes an underwater descattering framework integrating polarization physics with low-rank decomposition. First, a dynamic attenuation-regularized low-rank decomposition model is established, enabling adaptive parameter adjustment to separate background scattered light from target signals. Then, a nonlinear correlation equation for polarization-driven transmittance based on Beer-Lambert Law is developed, combining isotropic intensity attenuation transmittance through adaptive weighting mechanism to establish the composite transmittance, more in line with the underwater optical and physical characteristics Finally, a dual-constraint optimization architecture is designed to effectively suppress descattering noise. Experimental results demonstrate that our method achieves better imaging results and significant improvements in key metrics. This research establishes an innovative “underwater imaging-cross-domain migration” paradigm for scattering environment imaging, showing promising applications in marine exploration and intelligent navigation.