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Examining Alternatives to Wavelet Denoising for Astronomical Source Finding

Part of: Australian SKA Pathfinder

Published online by Cambridge University Press:  02 January 2013

R. Jurek  and
S. Brown
R. Jurek*
Affiliation:
CSIRO Astronomy & Space Sciences, Australia Telescope National Facility, PO Box 76, Epping, NSW 1710, Australia
S. Brown
Affiliation:
CSIRO Astronomy & Space Sciences, Australia Telescope National Facility, PO Box 76, Epping, NSW 1710, Australia
*
BCorresponding author. Email: russell.jurek@csiro.au
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Abstract

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The Square Kilometre Array and its pathfinders ASKAP and MeerKAT will produce prodigious amounts of data that necessitate automated source finding. The performance of automated source finders can be improved by pre-processing a dataset. In preparation for the WALLABY and DINGO surveys, we have used a test Hi datacube constructed from actual Westerbork Telescope noise and WHISP Hi galaxies to test the real world improvement of linear smoothing, the Duchamp source finder's wavelet denoising, iterative median smoothing and mathematical morphology subtraction, on intensity threshold source finding of spectral line datasets. To compare these pre-processing methods we have generated completeness-reliability performance curves for each method and a range of input parameters. We find that iterative median smoothing produces the best source finding results for ASKAP Hi spectral line observations, but wavelet denoising is a safer pre-processing technique. In this paper we also present our implementations of iterative median smoothing and mathematical morphology subtraction.

Keywords

methods: statisticalmethods: data analysisradio lines: galaxiestechniques: image processing
Type
Research Article
Information
Publications of the Astronomical Society of Australia , Volume 29 , Special Issue 3: Source Finding and Visualisation , 2012 , pp. 352 - 358
Copyright
Copyright © Astronomical Society of Australia 2012

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