## 4 PSIFTIS Imaging Experiment Results and Data Processing
### Infrared Polarization Image Fusion  
A carbon-silicon rod light source is used as the active light source with a polarizer attached behind. It is verified that the system has polarization components in each polarization direction, which meets the universality of instruments. Therefore, this paper takes a light source that simulates a polarization angle of 38\({}^{\circ}\) as an example for the study on polarization image fusion. The displacement between image units would occur due to the machining error of the micro-lens array in the system, and the crosstalk between interference channels would also make the brightness of image units uneven, which would affect the final imaging quality of the system. Therefore, it is necessary to extract useful information or features of each image and fuse them to improve the quality and clarity of the image. The polarization images of 0\({}^{\circ}\), 45\({}^{\circ}\), 90\({}^{\circ}\), and 135\({}^{\circ}\) obtained through experiments are preprocessed to obtain four infrared polarization images, as shown in Figure 12.  
Next, the polarization solution is performed by using the existing polarization images, and the DoP and AoP images are obtained as shown in Figure 13.  
Images of the PI, DoP, and AoP are obtained as shown in Figure 13a-c. Polarization image fusion is performed on DoP and AoP images by using the pixel-based image fusion mean value method, maximum value method, and minimum value method, and the results are shown in Figure 14.  
Figure 12: Images of four polarization angles after preprocessing: (**a**) 0\({}^{\circ}\) polarization; (**b**) 45\({}^{\circ}\) polarization; (**c**) 90\({}^{\circ}\) polarization; (**d**) 135\({}^{\circ}\) polarization. Figure 13: Polarization calculation image: (**a**) polarization intensity image (PI); (**b**) DoP; (**c**)AoP. It can be seen from subjective observation that the image of the minimum value fusion method is clearer and brighter, and the edge details are also enhanced, so this has the best imaging effect among the three methods. The objective index is evaluated by the PSNR (peak signal-to-noise ratio). The PSNR of the DoP image is 5.9090 dB, and the PSNR of the AoP image is 14.1327 dB. The PSNR of the mean value fusion image is 11.8186 dB, the PSNR of the maximum value fusion image is 8.0655 dB, and the PSNR of the minimum value fusion image is 14.7940 dB. It can be seen that the peak signal-to-noise ratio of the minimum value fusion image is higher than that of the other two fusion methods and higher than that of the AoP and DoP images. The PI and PF images obtained previously were decomposed into one low-frequency component and three high-frequency components by using the Haar wavelet transform, as shown in Figures 15 and 16. In order to verify the effectiveness of the fusion algorithm of the low-frequency region coefficient difference combined with average gradient grayscale stretching (RCD-AG-GS) in Section 3.2.3. (1) above, the fusion rule of taking the maximum of the region contrast, the maximum of the region energy, and the minimum of the region energy is selected to compare with the algorithm in this paper, and the objective evaluation function indexes such as average gradient (AG), peak signal-to-noise ratio (PSNR), information entropy (EN), and mutual information (MI) are used to quantitatively evaluate the quality of the fused image. Different low-frequency component fusion rules are shown in Figure 17, and the pairs of objective evaluation indexes are shown in Table 2.  
From the analysis of the objective evaluation function indexes of the fused image, the RCD-AG-GS fusion rules adopted in this paper have excellent performance in the root mean square error, peak signal-to-noise ratio, and mutual information indexes, which greatly outperform other fusion rules. In the information entropy index, they are basically equal to other methods and better than the initial two images. In order to verify the effectiveness of the fusion algorithm for the maximum value of high-frequency weighted area energy in Section 3.2.3.