## 3 Experiment Validation and Analysis
### Experiment and Analysis of the Geographic Polarization Suppression Model  
The experimental setup for glare suppression based on the geographic polarization suppression model is depicted in Figure 13. This setup includes a visible light monochrome camera, a rotatable polarizer, and an MEMS inertial sensor, with the experiment conducted outdoors in Changchun simulating a fluctuating sea area (coordinates: N 43\({}^{\circ}\)50\({}^{\prime}\)55\({}^{\prime\prime}\), E 125\({}^{\circ}\)23\({}^{\prime}\)55\({}^{\prime\prime}\)). During the experiment, the methods described in Sections 2.2.1 and 2.2.2 are used to calculate the light incidence angle at different  
We compared the polarization angles at the same incidence angles in Table 6 with those in Table 1, and calculated the relative error of the experimental data in Table 6 with respect to Table 1. The results of the relative error calculation are shown in Table 7.  
As indicated in Figure 14, in the glare suppression experiment using the geographic polarization model, the curve showing the relationship between the light incidence angle and the glare polarization angle approximates the correlation observed in Figure 8. According \begin{table}
\begin{tabular}{l l l} \hline \hline
**Time** & **Incidence Angle (\({}^{\circ}\))** & **Glare Polarization Angle (\({}^{\circ}\))** \\ \hline June 27 th, 18:16 & 10 & 98.85 \\ June 27 th, 17:47 & 15 & 97.23 \\ June 27 th, 17:18 & 20 & 95.95 \\ June 27 th, 16:49 & 25 & 95.00 \\ June 27 th, 16:22 & 30 & 94.40 \\ June 27 th, 15:54 & 35 & 94.13 \\ June 27 th, 15:26 & 40 & 94.21 \\ June 27 th, 14:58 & 45 & 94.58 \\ June 27 th, 14:29 & 50 & 95.26 \\ June 27 th, 14:00 & 55 & 96.27 \\ June 27 th, 13:28 & 60 & 97.62 \\ June 27 th, 12:51 & 65 & 99.31 \\ June 27 th, 11:45 & 70 & 101.33 \\ \hline \hline \end{tabular}
\end{table} 
Table 6: Glare suppression experiment based on geographic polarization suppression model. Figure 14: Geographic polarization suppression model glare suppression relationship curve between incidence angle and polarization angle. to Table 7, the average relative error of the glare polarization angle in the geographic polarization model glare suppression experiment is 11.81%. Therefore, the method proposed in this paper, based on glare suppression using the geographic polarization model, also demonstrates an incident-polarization correlation, further validating the effectiveness and feasibility of the proposed glare suppression method. Comparison curve of experimental data on polarization angle is shown in Figure 15.  
To verify the glare suppression effect of the method proposed in this paper, image quality assessment metrics were employed to measure the quality of image restoration after glare suppression. Common image quality assessment metrics include the mean squared error (MSE), peak signal-to-noise ratio (PSNR), and structural similarity index measure (SSIM). Although all three methods can evaluate images after glare suppression, MSE and PSNR only consider pixel-level differences and do not account for human visual perception of images. They are also very sensitive to minor changes in the image, which can lead to unreasonable evaluation results. On the other hand, SSIM is an image quality metric designed to evaluate the similarity between two images based on human visual perception. Its values range from 0 to 1, using the mean as an estimate of luminance, standard deviation as an estimate of contrast, and covariance as a measure of structural similarity, making its image quality evaluations more reasonable and accurate. Therefore, the SSIM method is used in this paper for image quality assessment. Table 8 shows the SSIM values for three sets of glare suppression experiment images. The comparison of the effects before and after glare suppression is shown in Figure 16. The three sets of glare suppression experiments were conducted on 14 August 2023, at 15:24; 15 August 2023, at 10:15; and 9 August 2023, at 14:29, respectively.