# 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
The camera is mounted onto a stratospheric balloon carrying a telescope. It is pointed towards the above sky and contains a lot of noise. Indeed, here the dust over the sensor's lenses, mesosphere wind turbulence and stray light from the Antarctic continent's albedo are clearly visible and cause a strong ghost noise which covers the few  
Figure 14: Juno Star Reference Unit’s [45] image segmentation (Credits to NASA): (**a**) real image, (**b**) LTA’s prediction; (**c**) LTS’ prediction; (**d**) the BOSS algorithm’s prediction. Figure 12: Italian Space Agency Matera Telescope’s image segmentation: (**a**) real image; (**b**) LTA’s prediction; (**c**) LTS’ prediction; (**d**) the BOSS algorithm’s prediction. Figure 13: E and B Experiment mission [44] star camera’s image detail segmentation: (**a**) real image; (**b**) LTA’s prediction; (**c**) LTS’ prediction; (**d**) the BOSS algorithm’s prediction. stars in the background. Recognizing stars in this condition is important because star sensors are not used just in space where the absence of atmosphere avoids many noise sources, but also on ships or cruise missiles for navigation purposes, where being able to remove ghost noise due to clouds and other atmospheric effects is mandatory. The LTA (b) algorithm's prediction shows that few of the brightest stars have been correctly segmented with a not complete filtering action of the noise in the top right part of the image noise. The LTS behaves worst because the strong noise scenario does not allow it to correctly segment the image. There is a lot of noise, with horizontal foreground streaks in addition to the correct segmented stars. This bad behavior is due to the algorithm's inability to adapt itself to different SN conditions. Here, a re-calibration of the algorithm threshold would provide a better segmentation quality for the mask. In the last image (d), the BOSS algorithm prediction shows the segmentation of all the brightest stars (red boxes) with just a little portion of noise in the most corrupted region. Both the LTA and the BOSS algorithm show some problems with the strong ghost noise conditions but in different regions of the image and in different ways: the BOSS algorithm seems to detect as stars the strong nonuniform brightest corrupted region due to the mesosphere winds in the image, while the LTA seems to have an opposite problem with the darker region in the top right part. The explanation for the BOSS algorithm is that the whitest spots in the ghost noise are recognized as possible embedded foreground objects, while in the LTA case, the gray level gradients in the darker localized region mislead the algorithm in properly segmenting the image. Among the two false positives cases, this LTA behaviour could greatly affect the output mask quality because the gradient in the darker region of the image (generally the 99 % of these samples) increases the percentage of noise in the output mask (with possible negative effects both for attitude determination routines and RSO detection). * Figure 14: This is a frame from a video [45] from Juno's Star Reference Unit (SRU) camera. The image contains stars and a huge number of SEU's crossing the sensor with different impact angles as the Juno spacecraft crosses Jupiter's high radiation polar regions. SEUs over images are caused by ionizing radiation which hits the sensor pixels. The more perpendicular to the sensor plane the ionizing radiation is, the more point-like the footprint of the high energy particle on the sensor will be. This noise source can be reduced by shielding the electronics properly, but it cannot be removed. In the analysed image, many SEUs cross the sensor due to the high energetic region where the Juno spacecraft is. It is quite difficult to distinguish the white spots nature, but the purpose of this image processing is to show how the weakest elements on the detector (certainly SEUs under spacecraft inertial pointing condition) are removed.