# Image Dehazing Enhancement Strategy Based on Polarization Detection of Space Targets
## 5 Image Dehazing Method Based on Full Polarization Information Inversion and Image Fusion
### Validation Based on Simulated Space Target Images  
To verify the effectiveness of the dehazing method proposed in our paper, the simulated space target polarization images were first used. In the preprocessing process, the HMIRCA method was used to solve the original polarization information, and the DPFE image was obtained using the image dehazing method based on full polarization information inversion and image fusion. In terms of subjective comparison, the proposed method is compared with several other classical dehazing methods, including the Polarization Difference Dehazing (PDD) method [8], multiscale Retinex method [27], and Dark channel priority (DCP) method [28]. The comparison results are shown in Figure 8.  
As shown in Figure 8, the distortion of the image after restoration was reduced using PDD method, but there is a problem of incomplete dehazing. The multi-scale Retinex method can be effectively used to reduce the effect of haze on image quality. The target contour features remain intact, but the image has a high degree of color distortion, and there are obvious ripple features in the image. The dehazing image obtained by the DCP method is dark, and the contour features are submerged, making it difficult to identify. Compared to the above methods, the influence of haze on image quality can be better eliminated by using our method. The detailed features can be preserved, and the contrast of the image is high, which can effectively highlight the characteristics of the space target to be measured.  
In terms of objective evaluation, the Peak signal-to-noise ratio (PSNR) and Structural Similarity (SSIM) were used to reflect the target structural integrity. Average Gradient (AG), Mean Value (MV), and Standard Deviation (SD) were also used to evaluate the image  
Figure 8: Subjective comparison results of the dehazing effects of simulated space targets.  
dehazing results; these indicators were used to reveal the quality of the image in terms of clarity, brightness, and contrast, respectively.  
The statistical results of the data in Table 2 show that in terms of PSNR and SSIM, the dehazing image obtained by using our method has the highest similarity with the structural features in the original image, indicating that the target structure before degradation can be better restored. In terms of AG, the value obtained by our method is significantly improved compared with the other three methods, indicating that the detail contour features in the image after enhancement are the most prominent. As for SD, the method proposed has the highest standard deviation among the three groups of dehazing images, indicating that the image obtained using our method has the highest contrast. In terms of MV, since the main purpose of using our method is to improve the image contrast and highlight the target features, the overall brightness of the target in the image is weaker than that in the multi-scale Retinex method. Although the brightness of the image background is reduced, the detailed characteristics of the target are highlighted, and the quality of the image is improved.