| My name is Lars Flöer and I'm a PhD student at the Argelander-Institut für Astronomie which is part of the University of Bonn, Germany. In my thesis I work on the extragalactic data from the Effelsberg-Bonn-HI-Survey. This includes developing methods for radio frequency interference mitigation, source extraction, compilation of a source catalog and statistical analysis of it.
During my stay at ASTRON I worked mostly with Paolo Serra on source finding for HI surveys. I've developed a new source finding algorithm based on wavelet transformations and partial reconstruction of the data and evaluated the performance of the algorithm using various simulated datasets. In addition I also worked with Paolo on an source finder that uses negative detections to assign a probability of being a true source to each detection. Both projects gave me the opportunity to meet other people from the source finding community and I made valuable contacts with people working on ASKAP, the australian SKA pathfinder.
Wavelet denoising is an increasing popular tool to remove noise from images and increase the signal-to-noise ratio. This example shows the application of a multidimensional wavelet denoising scheme to a simulated HI data cube. The left pane shows the simulated data, whereas the middle and right pane show only the inserted source and the denoised version of the simulated data, respectively. The latter image can be used to automatically extract sources from large data sets.