Asteroid detection using a single multi-wavelength CCD scan

Jonathan Melton

doi:10.1117/12.2237326

27 September 2016 Asteroid detection using a single multi-wavelength CCD scan

Jonathan Melton

Proceedings Volume 9971, Applications of Digital Image Processing XXXIX; 99710Z (2016) https://doi.org/10.1117/12.2237326
Event: SPIE Optical Engineering + Applications, 2016, San Diego, California, United States

Abstract

Asteroid detection is a topic of great interest due to the possibility of diverting possibly dangerous asteroids or mining potentially lucrative ones. Currently, asteroid detection is generally performed by taking multiple images of the same patch of sky separated by 10-15 minutes, then subtracting the images to find movement. However, this is time consuming because of the need to revisit the same area multiple times per night. This paper describes an algorithm that can detect asteroids using a single CCD camera scan, thus cutting down on the time and cost of an asteroid survey. The algorithm is based on the fact that some telescopes scan the sky at multiple wavelengths with a small time separation between the wavelength components. As a result, an object moving with sufficient speed will appear in different places in different wavelength components of the same image. Using image processing techniques we detect the centroids of points of light in the first component and compare these positions to the centroids in the other components using a nearest neighbor algorithm. The algorithm was used on a test set of 49 images obtained from the Sloan telescope in New Mexico and found 100% of known asteroids with only 3 false positives. This algorithm has the advantage of decreasing the amount of time required to perform an asteroid scan, thus allowing more sky to be scanned in the same amount of time or freeing a telescope for other pursuits.

Conference Presentation

Citation Download Citation

Jonathan Melton "Asteroid detection using a single multi-wavelength CCD scan", Proc. SPIE 9971, Applications of Digital Image Processing XXXIX, 99710Z (27 September 2016); https://doi.org/10.1117/12.2237326

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