Speaker Name: Aaron Luttman (aluttman at clarkson dot edu )
Speaker Afiliation: Clarkson University
Abstract: Pictures taken by telescopes on the ground - like those at Kitt Peak in Arizona or Mauna Kea in Hawaii - suffer from two primary problems.
The first is that the images are noisy. This means that random errors cause the picture to not look like the real scene of outer space. The second problem is that the pictures are blurry, which is a systematic (i.e. not random) phenomenon caused by the atmosphere. It turns out that we can mathematically "undo" the problems of noise and blur by using a mathematical model that looks a lot like a problem in linear algebra. In fact, some of the basic ideas of solving linear systems in linear algebra can be applied directly to find out what the picture would look like if there were no problems with noise and blur, given only a few basic assumptions about what the objects we're looking at really look like.
Target Audience: This presentation is aimed at students (or faculty) who have some background in linear algebra or at least solving linear systems of equations.
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