An Efficient Profile Detection Method for Fiber Spectrum Images with Low SNR Based on Wigner Bispectrum
Jia Zhu A , Zhangqin Zhu A and Zhongfu Ye A BA Institute of Statistical Signal Processing, Department of Electronic Engineering and Information Science, University of Science and Technology of China, Hefei 230027, China
B Corresponding author. Email: yezf@ustc.edu.cn
Publications of the Astronomical Society of Australia 28(2) 144-149 https://doi.org/10.1071/AS11012
Submitted: 29 November 10 Accepted: 4 March 11 Published: 22 June 2011
Abstract
A novel profile detection method is proposed for astronomical fiber spectrum data with low signal-to-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 spectrum signal 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: profiles — methods: data analysis — techniques: spectroscopic
References
Benesty, J., Chen, J. D. and Huang, Y. T., 2008, IEEE Trans. Audio Speech Lang. Process., 16(4), 757| Crossref | GoogleScholarGoogle Scholar |
Blondin, S., Walsh, J. R., Leibundgut, B. and Sainton, G., 2005, , 431, A&A, 431, 757
| Crossref | GoogleScholarGoogle Scholar |
Chernogor, L. F., Lazorenko, O. V. & Vishnivezky, O. V., 2006, in Proc. Int. Conf. Ultrawideband Ultrashort Impulse Signals 3, 297
Cui, B., Ye, Z. F. and Bai, Z. R., 2008, AcASn, 49(3), 327
de Boer, K. S. and Snijders, M. A. J., 1981, IUENN, 14, 154
Fonollosa, J. R. and Nikias, C. L., 1991, in ICASSP, 5, 3085
Gerr, N. L., 1988, Proc. IEEE, 76(3), 290
| Crossref | GoogleScholarGoogle Scholar |
Horne, K., 1986, PASP, 609, 617
Marsh, T. R., 1989, PASP, 98, 609
Piskunov, N. E. and Valenti, J. A., 2002, , 385, A&A, 385, 1095
| Crossref | GoogleScholarGoogle Scholar |
Pych, W., 2004, PASP, 116, 148
| Crossref | GoogleScholarGoogle Scholar |
Rhoads, J. E., 2000, PASP, 112, 703
| Crossref | GoogleScholarGoogle Scholar |
Robertson, J. G., 1986, PASP, 1220, 1231
Sanchez, S. F., 2006, AN, 327, 850
Ville, J., 1948, Cables Transm., 2A, 61
Wigner, E. P., 1932, PhRv, 40, 749
Zhu, Z. Q., Zhu, J. and Ye, Z. F., 2010, Image Signal Process., 3, 4118