## 3 AS01 SAR Satellite Data Experiment and Analysis
### Performance Evaluation Based on Wake Detection  
Meanwhile, the evaluation method for ship wake enhancement processing based on Radon transform involves detecting the SAR wake image using Radon transform, detecting peaks/valleys in the transformed domain, and comparing the intensity of wake characteristics in the evaluated image to assess the effectiveness of the ship wake enhancement algorithm. Theoretically, the better the wake enhancement processing, the stronger the linear characteristics of the wakes in the image, leading to larger peaks in the corresponding transform space. For the evaluation of ship wake enhancement processing in the pre- and post-processed wake image data in Figure 6, a rectangular mask is used to cover bright spots caused by non-wakes, which may adversely affect the results of the Radon transform \begin{table}
\begin{tabular}{c c c} \hline
**Evaluation Criteria** & **Original Wake Image** & **Enhanced Wake Image** \\ \hline Equivalent number & 3.22 & 7.37 \\ Information entropy & 5.21 & 1.71 \\ \multirow{3}{*}{Visual effect} & Dim brightness with & \\  & unclear wake features & \\  & Discontinuous & \\  & wake features & \\ \hline \end{tabular}
\end{table} 
Table 2: Image quality evaluation results. based algorithm. The mask frame is a rectangle centered on the ship, with its size set in the azimuth direction as \(2a\); \(a\) is determined based on the expected maximum azimuth offset due to relative motion [30]. To facilitate the display of the Radon transform domain's effect, the image is rotated by \(90^{\circ}\), so that the direction of the wakes in the image becomes horizontal. Consequently, the angles corresponding to the wake features in the Radon transform are centered near the middle of the angle axis. In the application of ship wake detection, due to the presence of speckle noise in SAR images, it is usually necessary to use preprocessing methods, such as filtering, to preprocess the original image and then carry out relevant transformations and detection processing. In this paper, median filtering is also used to enhance the image wake. The results are shown below. According to Figure 6, in the original spaceborne SAR image, there is a wake phenomenon at the stern of the ship, and the wake direction extends along the azimuth. Therefore, after converting to the Radon transform domain, as shown in Figure 6a, there are bright peak points appearing in the regions corresponding to \(83^{\circ}\)-\(85^{\circ}\) and \(90^{\circ}\)-\(92^{\circ}\), which are consistent with the actual wake direction. Comparing Figure 6a-c, the peak points in the radon transform domain of the original wake image are weaker. After median filtering, there was no significant change. However, after the wake enhancement processing based on OSMI images, the focus of peak points in the Radon transform domain is more pronounced. The intensity of peak points in the Radon transform domain was compared, and the results are shown in Table 3.  
Figure 6: _Cont._  
Based on the wake enhancement processing results of OSMI, the evaluation was conducted using the Radon transform. After the enhancement process, the peak intensity in the Radon domain corresponding to the ship wake was improved by approximately 2.6 dB. This enhancement can contribute to improving the reliability and directional accuracy of wake detection. Furthermore, it can be observed that after filtering processing under complex sea conditions, the intensity of the peaks in the Radon transform domain does not show significant changes, which is similar to the visual effect. The reason for this is that the filtering process mainly reduces speckle noise, while its impact on integral processing in a certain direction, such as the Radon transform, is limited. In wake detection processing, especially under conditions of complex sea states or poor wake imaging conditions, it is necessary to perform clustering on the detected local peak points.