Hostname: page-component-8448b6f56d-qsmjn Total loading time: 0 Render date: 2024-04-24T11:25:40.359Z Has data issue: false hasContentIssue false
  • English
  • Français

An Efficient Profile Detection Method for Fiber Spectrum Images with Low SNR Based on Wigner Bispectrum

Published online by Cambridge University Press:  02 January 2013

Jia Zhu ,
Zhangqin Zhu  and
Zhongfu Ye
Jia Zhu
Affiliation:
Institute of Statistical Signal Processing, Department of Electronic Engineering and Information Science, University of Science and Technology of China, Hefei 230027, China
Zhangqin Zhu
Affiliation:
Institute of Statistical Signal Processing, Department of Electronic Engineering and Information Science, University of Science and Technology of China, Hefei 230027, China
Zhongfu Ye*
Affiliation:
Institute of Statistical Signal Processing, Department of Electronic Engineering and Information Science, University of Science and Technology of China, Hefei 230027, China
*
BCorresponding author. Email: yezf@ustc.edu.cn
Rights & Permissions [Opens in a new window]

Abstract

Core share and HTML view are not available for this content. However, as you have access to this content, a full PDF is available via the ‘Save PDF’ action button.

Anovel profile detection method is proposed for astronomical fiber spectrum data with low signalto-noise ratio. This approach can be applied to the pretreatment for 2-D astronomical spectrum data before the extraction of spectra. The Wigner bispectrum, a classical higher-order spectrum analysis method, is introduced and applied to deal with the spectrumsignal in this article.After analyzing the Wigner higher-order spectra distribution of the target profile signal, the combination of the Wigner bispectrum algorithm and the fast Fourier transform algorithm is used to weaken the effect of the noise to obtain more accurate information. Both the reconstruction method of the Wigner bispectrum and inverse fast Fourier transform are used to acquire the detection signal. At the end of this paper, experiments with both simulated and observed data based on the Large Sky Area Multi-Object Fiber Spectroscopy Telescope project are presented to demonstrate the effectiveness of the proposed method.

Keywords

line: profilesmethods: data analysistechniques: spectroscopic
Type
Research Article
Information
Publications of the Astronomical Society of Australia , Volume 28 , Issue 2 , 2011 , pp. 144 - 149
Copyright
Copyright © Astronomical Society of Australia 2011

References

Benesty, J., Chen, J. D. & Huang, Y. T., 2008, IEEE Trans. Audio Speech Lang. Process., 16(4), 757CrossRefGoogle Scholar
Blondin, S., Walsh, J. R., Leibundgut, B. & Sainton, G., 2005, A&A, 431, 757Google Scholar
Chernogor, L. F., Lazorenko, O. V. & Vishnivezky, O. V., 2006, in Proc. Int. Conf. Ultrawideband Ultrashort Impulse Signals 3, 297Google Scholar
Cui, B., Ye, Z. F. & Bai, Z. R., 2008, AcASn, 49(3), 327Google Scholar
de Boer, K. S. & Snijders, M. A. J., 1981, IUENN, 14, 154Google Scholar
Fonollosa, J. R. & Nikias, C. L., 1991, in ICASSP, 5, 3085Google Scholar
Gerr, N. L., 1988, Proc. IEEE, 76(3), 290CrossRefGoogle Scholar
Horne, K., 1986, PASP, 609, 617Google Scholar
Marsh, T. R., 1989, PASP, 98, 609Google Scholar
Piskunov, N. E. & Valenti, J. A., 2002, A&A, 385, 1095Google Scholar
Pych, W., 2004, PASP, 116, 148CrossRefGoogle Scholar
Rhoads, J. E., 2000, PASP, 112, 703CrossRefGoogle Scholar
Robertson, J. G., 1986, PASP, 1220, 1231Google Scholar
Sanchez, S. F., 2006, AN, 327, 850Google Scholar
Ville, J., 1948, Cables Transm., 2A, 61Google Scholar
Wigner, E. P., 1932, PhRv, 40, 749Google Scholar
Zhu, Z. Q., Zhu, J. & Ye, Z. F., 2010, Image Signal Process., 3, 4118Google Scholar