Artefact Detection In Astrophysical Image Data Using Independent Component Analysis

TL;DRAbstract

This paper is the first reported application of ICA on astrophysical image data. When studying far-out galaxies from a series of consequent telescope images, there are several sources for artefacts that influence all the images such as camera noise, atmospheric fluctuations and disturbances, and stars in our own galaxy. For this problem, the linear ICA model holds very accurately, because the independence of such artefacts is guaranteed. Using image data on the M31 Galaxy, it is shown that several clear artefacts can be detected and recognized based on their temporal pixel luminosity profiles and independent component images. Once these are removed, it is possible to concentrate on the real physical events like gravitational lensing. ICA might provide a very useful preprocessing for the large amounts of available telescope image data.

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