A Computer Vision Approach for the Detection of Asteroids/Comets in Space Satellite Images

TARGET GROUP: ASTEROIDS/COMETS

OBJECTIVES         

·        To find moving targets such as asteroids and comets in NEOSSAT images by the use of computer vision algorithms by detecting the comets/asteroids that are only %2 different in brightness with respect to the background.

·        To detect not only small and dim moving targets, but also to detect non-linear trajectories.

SUMMARY

The Earth had an experience of a huge crash with an asteroid which resulted in the disappearance of the dinosaurs. While that accident happened a long time ago, a recent similar incident for Jupiter was a reminder alarm that such catastrophes could happen again to the Earth. 25 years ago, there was a collision between a comet and Jupiter which significantly affected its atmosphere for several days. This comet, Shoemaker-Levy 9 (SL9), had been discovered about one year before the accident happened (Hille, 2019). Thus, not to neglect the likely devastating impact of such events, it is vital to observe the space consistently and look for all moving objects, especially those moving near the Earth. Recently, scientists were amazed by observing two interstellar objects passing through the solar system. One of them was an asteroid named Oumuamua seen in 2017 (Dunford, 2019), and one of them was a comet named 2I/Borisov seen in 2019 (Garner, 2019). These are the two first unique interstellar objects detected in the solar system. Being able to find these objects, it would be possible to explore not only the solar system and other planets but also the universes outside the solar system. To detect asteroids and comets, as moving targets, several algorithms are applied. These algorithms can be categorized as three main approaches as the basic technique, shift and add technique, and streak detection technique (Anthony, Emami, 2018). In basic techniques, two images taken from one location in two different times are subtracted. To find out the moving targets, the method looks for peaks in the difference image. As there are a lot of noises in the sky images, recognizing moving targets becomes impossible sometimes in cases that the asteroids or comets in the images are not large or bright enough to be differentiated from noises.

REFERENCE

https://www.int-arch-photogramm-remote-sens-spatial-inf-sci.net/XLIII-B3-2020/1185/2020/isprs-archives-XLIII-B3-2020-1185-2020.pdf