Two-dimensional Spectrum Extraction Method Based on Sparse Reconstruction Algorithm for LAMOST Real Data
According to the characteristics of the real data on the Large Sky Area Multi-Object Fiber Spectroscopic Telescope (LAMOST),a two-dimensional (2-D) spectrum extraction method based on sparse reconstruction algorithm is proposed.The proposed method uses the corresponding flat-field images and calibration lamp images,respectively,to build the 2-D Gauss model.Then,a sparse reconstruction algorithm with dual constraints is used to solve the inverse process of the formation of the 2-D observed spectra,restoring the original one-dimensional (1-D) spectrum.The experiments show that the proposed method reduces the extension of the spectra contours,contrasted with the 1-D method,and suppress the ringing problem of the pre-existing methods,getting more accurate extracted results.Besides,the proposed spectrum extraction method can be used on other telescope survey systems as well since the spectra formation mechanism of them are similar.
LAMOST real data spectrum extraction sparse reconstruction 2-D Gauss model
Bo Zhang Zhongfu Ye Xu Xu
Department of Electronic Engineering and Information Science, University of Science and Technology of China Hefei 230027, P.R. China
国际会议
秦皇岛
英文
297-301
2015-09-18（万方平台首次上网日期，不代表论文的发表时间）