The Big Bang-up

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Michael Hobson

About our expert

Dr Michael Hobson graduated from Cambridge University with a First Class Honours in Natural Sciences and was awarded a Ph.D. from the Astrophysics Group of the Department of Physics. Whilst working as a post-doctoral researcher at Cambridge, he became interested in cosmology and, in particular, making observations of the cosmic microwave background (CMB - the `afterglow' of the big bang). This is where he began his work on astronomical image reconstruction techniques, and was involved in producing the most detailed map of the CMB up to that date. Following his Research Fellowship, he was elected to a full Staff Fellowship at Trinity Hall, where he teaches Physics and Mathematics to undergraduates, and was also awarded a 5-year Advanced Fellowship by the Particle Physics and Astronomy Research Council to continue his reseach in cosmology at the Astrophysics Group in Cambridge. Michael began working on the CCTV images in 1999 and was awarded a 3-year NESTA Fellowship to pursue this work in October 2000.

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"Have you ever wondered how astronomers produce those wonderful pictures that appear in the papers or on television from time to time? They certainly look very impressive, but in many cases it has taken a lot of work to turn the signal received by the telescope into a clear image of a star cluster or distant galaxy.

The basic images produced by telescopes often bear only a passing resemblance to the final pictures presented in the media or scientific journals. These `raw data' (as they are called) usually suffer from `blurring' and `noise' caused by the inevitable imperfections inherent in any measurement process. Therefore, an important part of modern astronomy is to develop ways of processing the raw data to remove these unwanted artefacts, and produce a clear picture, worthy of a slot on the Ten O'Clock News.

As an astronomer working in the Cavendish Astrophysics Group in Cambridge for the last 10 years, I have been very closely involved in developing a wide variety of `image reconstruction' techniques. These are basically mathematical algorithms that run on a (usually very large) computer. The program reads in the blurred, noisy data and attempts to reconstruct the actual image the telescope observed (which we generally call `the truth').

It is likely that I would still be working solely in the analysis of astronomical images if I hadn't sat down one evening with a cup of tea and happened across an episode of Crimewatch on television. In one particular item, a man had walked into a Post Office, threatened the cashier and made off with a considerable sum of money. Fortunately, the man has been caught on the CCTV camera. Unfortunately, as is often the case, the picture was terrible. It was so blurred that it was impossible to make out the man's features. Suddenly, I realised that the techniques I had developed for reconstructing astronomical images might work equally well at enhancing pictures like those taken by the CCTV camera.

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