# Image Dehazing Enhancement Strategy Based on Polarization Detection of Space Targets
## 3 Hybrid Multi-Channel Interpolation Method Based on Regional Correlation Analysis  
Due to the limitations of the manufacturing process, there are differences in the parameters of micropolarizer in MPA [15], resulting in instantaneous field of view errors. The instantaneous field of view error can seriously affect the solution of polarization information, introducing incorrect polarization information and noise. At present, the algorithms for reducing the instantaneous field of view error of polarization images mainly include interpolation algorithms, machine modeling algorithms, and deep learning algorithms [16]. Interpolation algorithms are more widely used due to their higher algorithm execution efficiency [17]. Interpolation algorithms include bilinear interpolation algorithm, nearest neighbor interpolation algorithm, and spline interpolation algorithm. Compared with the other two methods, the bilinear interpolation algorithm has a better effect on reducing the instantaneous field of view error [18]. However, when the bilinear interpolation method is used to process polarization images of dark and weak targets, although it can reduce the impact of the instantaneous field of view errors to a certain extent, the pseudo polarization edges of high texture areas in the image are revealed after interpolation reconstruction. Polarization images of space targets usually need to be collected under dark and weak imaging conditions; when under haze conditions, the accuracy of target polarization information calculation will be seriously affected by pseudo polarization edges. To overcome this problem and improve the detection capability of the detection system under haze conditions, a Hybrid Multi-channel Interpolation method based on Regional Correlation Analysis (HMIRCA) is proposed for the preprocessing process of space target polarization image dehazing. The reason why the bilinear interpolation method introduces the pseudo polarization edge phenomenon is mainly due to the fact that the relationship of the detection direction between the polarization component of a single pixel and the surrounding pixels is not fully considered. Actually, the polarization component of any single pixel has an important influence on estimating the polarization component in other directions. To fully consider the relationship between any pixels, the correlation coefficient \(\delta\) is used in the HMIRCA algorithm to improve the accuracy of polarization information calculation. The correlation coefficient between pixels is defined differently depending on the position of the pixel arrangement. The processing flow of the HMIRCA algorithm is as follows:  
Step 1: Assuming a pixel unit is used as the center pixel of a 3 \(\times\) 3 region, based on different polarization directions, the correlation coefficients corresponding to each pixel unit in the neighborhood of other pixels are calculated. Step 2: Normalize the correlation coefficients and they are used as interpolation coefficients. Step 3: Calculate the pixel values of the other three polarization direction pixel units within the 3 \(\times\) 3 region, except for the central pixel. Step 4: Complete the information calculation of all pixel units within the 3 \(\times\) 3 region, and continue to calculate the pixel information of adjacent 3 \(\times\) 3 region according to Step 1-3. Step 5: Calculate the pixel values of edge pixels in the image. In the polarization image of the space target, because most of the edge pixels are the sky background, the requirement of the extraction accuracy of these pixels is low. Therefore, in the method proposed in this paper, the bilinear interpolation method is used to complete the interpolation of edge pixels in order to improve operation efficiency.