# Towards Automatic Recognition of Wakes Generated by Dark Vessels in Sentinel-1 Images
## 3 Results
### Detection Performance Estimation  
The proposed approach is applied to assess the detection performance in all the scenarios introduced in Section 3.1. The tile of Figure 2a is exported from SNAP as a tiff image and processed in the MATLAB(r) environment. The white dots in Figure 5a are the points in which the merit indexes are estimated during the Step 1, i.e., all the positions of the scanning window over the tile. The red circles, instead, identify the pixels satisfying Equation (3), thus providing the candidate wake positions. Figure 5: Scenario 1 (5000 \(\times\) 3000 pixels, 50 km \(\times\) 30 km). (**a**) candidate wake positions based on Equation (3); (**b**) recognized wakes, i.e., image pixels crossed by the maximum number of candidate wakes; (**c**,**d**) example of reconstructed recognized wakes. It is possible to note a concentration of red circles around the true position of the wakes but also a large number of sparse candidate positions within the tile. As foreseen in Step 3, in each red circle, the wake is reconstructed thanks to the knowledge of (\(\theta\),\(s\)) pair and the blue pixels in Figure 5b are the pixels crossed by the largest number of reconstructed wakes. The locations of blue pixels enable the local wake detection analysis as in [25], whose outcomes are shown in Figure 5c-d for ship 247056100 and 636014645, respectively. Scenario 1 is characterized by homogenous wind speed condition and sea clutter and results confirm that this is the best case for the wake pattern recognition. Indeed, no wake is lost, and no false detections are identified. Moreover, the blue pixels are almost distributed along a line. The tile under analysis for assessing the detection performance in case of sea affected by natural surface film is shown in Figure 6a. Similar to the previous case, the candidate wake positions (red circle) are concentrated around the real wakes, but the presence of dark strips due to the surface film generates additional and false candidate wake positions. The blue pixels in Figure 6b suggest that the validation of the wake presence among neighbor pixels is an effective mean to discard such false wake positions. However, as a result of the trade-off between false and missed detections, the wake of ship 672269000 is not clearly distinguishable, so that it is not recognized. A local wake analysis around blue pixels in Figure 6b enables the wake reconstruction for ship 247036100, as shown in Figure 6c. Figure 6: _Cont._  
The tile selected for testing the scenario 2 (Figure 6a) is particularly interesting since it includes a very small dark vessel. Since during the step 1 the ship is masked to avoid that its returns affect the Radon-domain processing, the correct detection of such wake is an example of the operative application of the proposed approach. In details, assuming that the AIS data of the ships are exploited to classify the ships 247036100 and 672269000 as collaborative, the application of the proposed technique has enabled the detection of a non-collaborative ship by means of its wake. The local wake analysis shown in Figure 6d confirms the presence of the wake related to the dark vessel. Finally, it is worth noting that the blue pixels represent pixels crossed by the largest number of reconstructed wakes, i.e., pixel with the high level of confidence that they are crossed by wakes. If a lower level of confidence is acceptable, the wake of ship 672269000 is partially detected, but at the time, false alarms also result from portions of dark features on the sea surface. As far as the influence of dark sea area on the detection performance is concerned, Figure 7a shows that no concentration of candidate wake positions is due to bright spot over a dark background in the low wind speed area, which could have led to false detections. The detection results (Figure 7b) enable the identification of the wake, and no false detections are related to the dark sea. However, it is worth noting that in this case there is a gradual increase in wind speed from the dark area to the bright one.