A Measurement Angle Error Correction Method for Polarized Images Based on Levenberg-Marquardt.

To address the issue of error accumulation arising from the continuous rotation of polarizers within the polarization rotation table, this paper proposes a computational methodology for determining the true rotation angle of polarizers in instances where the rotation angle is unknown. From obtaining atmospheric polarization data, we delve into the relationship between the incident and outgoing light as it traverses optical components, assuming knowledge of the initial polarization state. Furthermore, we expound on the transformational relation between Stokes vectors and Mueller matrices. We leverage these foundational theories to attain precise atmospheric polarization information for multiple pixels. To mitigate the cumulative errors arising from the continuous rotation of polarizers, we use a nonlinear least squares optimization approach to determine polarization rotation angles in the images accurately. Additionally, this innovative approach was compared with the Gauss-Newton method. Simulation results clearly show that, under identical conditions, the algorithm described in this paper surpasses the Gauss-Newton method regarding precision, iteration count, and efficiency. Experimental validation unequivocally affirms the efficacy of the proposed algorithm in precisely estimating polarization rotation angles in images, a pivotal component for the subsequent meticulous reconstruction of atmospheric polarization patterns.