A deconvolution method based on adaptive Landweber iteration to extract LAMOST one-dimensional spectra. Issue 2 (16th January 2019)

• Record Type: Journal Article
• Authors: Li, Min; Li, Guangwei; Lv, Ke; Duan, Fuqing; Haerken, Hasitieer; Zhao, Yongheng
• Is Part Of: Monthly notices of the Royal Astronomical Society. Volume 484:Issue 2(2019)
• Page Start: 2403
• Page End: 2410
• Publication Date: 2019-01-16
• Subjects: instrumentation: spectrographs -- methods: numerical -- techniques: image processing -- techniques: spectroscopic; Astronomy -- Periodicals; Periodicals; 520.5
• DOI: 10.1093/mnras/stz133
• Languages: English
• ISSNs: 0035-8711

Abstract

Abstract: In this paper, we present a deconvolution algorithm based on adaptive Landweber iteration (ALI) to extract the one-dimensional (1D) 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 ∼25 per cent higher than those extracted using the traditional method, and it is obvious that the S/N ratio is also improved.