A deconvolution method based on adaptive Landweber iteration to extract LAMOST one-dimensional spectra
MONTHLY NOTICES OF THE ROYAL ASTRONOMICAL SOCIETY(2019)
摘要
In this paper, we present a deconvolution algorithm based on adaptive Landweber iteration (ALI) to extract the one-dimensional ( ID) spectra from Large Sky Area Multi-Object Fiber Spectroscopy Telescope (LAMOST) multi-fibre spectrum images. The algorithm can eliminate serious crosstalk and depress the noise from two-dimensional (2D) images by using adaptively selected regularization parameters. Experiments on simulated images illustrate that 2D residuals reach CCD noise level and that the signal-to-noise (S/N) ratios of the resulting 1D spectra are higher than those from traditional methods. Application on a real LAMOST image shows that the resolutions of 1D spectra extracted from our algorithm are similar to 25 per cent higher than those extracted using the traditional method, and it is obvious that the S/N ratio is also improved.
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关键词
instrumentation: spectrographs,methods: numerical,techniques: image processing,techniques: spectroscopic
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