Today, image denoising by thresholding of wavelet coefficients is a commonly
used tool for 2D image enhancement. Since the data product of spectroscopic
imaging surveys has two spatial and one spectral dimension, the techniques for
denoising have to be adapted to this change in dimensionality. In this paper we
will review the basic method of denoising data by thresholding wavelet
coefficients and implement a 2D-1D wavelet decomposition to obtain an efficient
way of denoising spectroscopic data cubes. We conduct different simulations to
evaluate the usefulness of the algorithm as part of a source finding pipeline.Comment: 8 pages, 7 figures, 1 table, accepted for publication in PASA Special
Issue on Source Finding and Visualizatio