## 3 Experiment Validation and Analysis
### Experiment and Analysis of the Geographic Polarization Suppression Model
For these experiments,  
Figure 15: Comparison curve of experimental data on polarization angle. \begin{table}
\begin{tabular}{l l l} \hline \hline  & \multicolumn{1}{c}{**Dynamic Polarization**} & \multicolumn{1}{c}{**Combined Dynamic Polarization**} \\  & **Control** & **Control and Pixel Normalization** \\ \hline Group1 & 0.8438 & 0.8586 \\ Group2 & 0.8056 & 0.8775 \\ Group3 & 0.8703 & 0.9209 \\ \hline \hline \end{tabular}
\end{table} 
Table 8: SSIM values for glare suppression image quality evaluation. the SSIM values for the images post-suppression using the dynamic polarization control adaptive suppression method based on the geographic polarization model compared to the original images without glare are 0.8438, 0.8056, and 0.8703, respectively. When combining the dynamic polarization control based on the geographic polarization model with the polarization pixel normalization glare suppression method, the SSIM values are 0.8586, 0.8775, and 0.9206, respectively. In all three sets of experiments, both the adaptive suppression method based on the geographic polarization model and the combined method with pixel normalization effectively restored the glare images, with SSIM values above 0.8. The SSIM values of the combined method are noticeably higher than those of the adaptive suppression method alone, indicating that the method proposed in this paper, which combines the geographic polarization model with pixel normalization for glare suppression, performs better in image restoration, offering more effective and realistic glare suppression results. The three sets of glare suppression experiments shown in Figure 16 were conducted on a small maritime floating platform, limited by the experimental environment, thus taking place in a small area of maritime space. However, the sea surface glare suppression method proposed in this paper can be applied to spatial sections of any size, meaning the effectiveness of the glare suppression is independent of the size of the spatial section. Changes in maritime wind force directly affect the classification of sea waves and the intensity of sea surface fluctuations. The glare suppression experiments in this paper were conducted under conditions of moderate wind force, which is compatible with the environment of sea waves ranging from level 0 to 3. According to the experimental results presented in this paper, the proposed glare suppression method maintains good performance under such wave conditions. However, as the wave level increases to levels 4 to 5, the performance of the dynamic polarization glare suppression method decreases due to the response speed of the adaptive dynamic polarization control being unable to meet the rate of change in sea surface fluctuations. Although the pixel normalization method proposed in this paper can compensate to some extent for the glare not suppressed due to the reduced performance of dynamic polarization control, there is a certain degree of reduction in the SSIM value of the image after glare suppression processing. When the wave level rises to levels 6 to 9, which correspond to extreme maritime weather conditions,  
Figure 16: Glare suppression experiment results. the inertial stability capacity of the experimental platform is insufficient and the response speed of adaptive polarization control is slow, resulting in a significant decrease in the performance of the glare suppression method proposed in this paper. Therefore, while the proposed glare suppression method is effective in suppressing sea surface glare in normal maritime environments, it is challenging to achieve effective suppression of sea surface glare under extreme maritime conditions.