Recovery of polarization information in scattering scenes based on Monte Carlo algorithm

We propose a Monte Carlo-based method for recovering polarization information in scattering scenes. This approach introduces a backscattering model to characterize polarization state variations within scattering media. Specifically, the Monte Carlo algorithm is employed to construct a computational model for simulating and analyzing the backscattering process of incident light within the scattering medium. By leveraging the mathematical relationship between the Stokes vector and the Mueller matrix, we mitigate the effects of backscattering on polarization information. The efficacy of the proposed methodology is validated through experiments. The findings demonstrate that the proposed method successfully recovers target polarization information while achieving enhanced imaging contrast compared to conventional polarization-difference imaging techniques.