# Design and Validation of a U-Net-Based Algorithm for Star Sensor Image Segmentation
## 3 Results
### BOSS Algorithm Comparison with Traditional Image Segmentation Algorithms
#### 3.4.2 Comparison Results  
Otsu's algorithms is the only traditional one which does not need any configuration of parameters. Its F1 score is 0.07%. The best achieved F1 values for every algorithm are summarized in Table 8 for a fast comparison. From previous tables, it can be seen that the best F1 score was achieved by the LTA algorithm followed by the LTS one and the BOSS algorithm. Niblack and Otsu behaved worse than the others, while the WIT achieved high but not satisfying performances. Both LTA and LTS behave better on the test set if compared to the BOSS algorithm. As a first impression, it would seem that the use of BOSS algorithm does not bring any advantage. However, the performances achieved by LTA and LTS were obtained via a tuning of their parameters, while the BOSS algorithm was not tuned after its design. LTA and LTS have to be calibrated every time the noise level changes inside the selected scenario to achieve the best segmentation quality output, while the BOSS algorithm does not need this calibration because it has been trained to segment well with several SN levels. This consideration means that the 69% of F1 index is a generalized performance value, while the 79% and 72% values for the traditional algorithms are optimized and not generalized. LTA and LTS were tuned against the test set, while the BOSS did not need any tuning. This would mean that a star tracker based on the BOSS algorithm would not require any calibration or segmentation performance degradation during its lifetime in orbit. Even if the sensor's noise increases with the increasing of the lifetime, the U-Net would be able to adapt itself to several levels of SN ratio because it has been trained to do so. A stray light or a higher radiative region would not affect the quality of the segmentation product very much. With this consideration, the strength and meaning of the BOSS performance can be more appreciated and understood. In Figures 12-14, it is possible to visually compare the segmentation algorithms output quality of these LT approaches and the BOSS algorithm to understand the limit of a traditional parameterized segmentation algorithm. Three real images of the night sky both from Earth and space were considered with different kinds and levels of noises. A discussion follows for each of them. \begin{table}
\begin{tabular}{c c c c} \hline
**F1 (\%)** & \(\mathbf{B}KG_{0}=\mathbf{1000}\) & \(\mathbf{B}KG_{0}=\mathbf{1500}\) & \(\mathbf{B}KG_{0}=\mathbf{200  
Considering the processing of these three figures:  
* Figure 12: In the real image, two geostationary satellites (green boxes) on the bottom part of the image are clearly visible with the surrounding star field. This image was obtained via the telescope of the Italian Space Agency Matera Observatory. The noise that mostly appears in this image is a nonuniform flare all over the image stronger in the bottom part and weaker in the top. It is due both to telescope lenses and nearby city light pollution. It is an example of ghost noise. The noise sources associated with the sensor electronics are negligible due to the sensor cooling system which was keeping the camera at \(-20\) \({}^{\circ}\)C. There are foreground horizontal and short streaks on the top left and top right edges of the image produced by the LTA algorithm. Moreover, there is some noise that has not been filtered in the whole image, together with the brightest and weakest objects. The same problem is present in LTS' prediction with a greater percentage of noise. Here, the best output quality is provided by the BOSS algorithm which correctly returns the most salient star-like objects, together with precious RSOs information. All the algorithms return the two small streaks of the geostationary. The stars in the background have a magnitude lower than 12. The used optics is an Officina Stellate RiFast 400 Telescope with a focal length of 1520 mm and an f-number of f/3.8. * Figure 13: The real image is a detail of a frame from the EBEX mission star camera [44].