OSA's Digital Library

Applied Optics

Applied Optics

APPLICATIONS-CENTERED RESEARCH IN OPTICS

  • Editor: Glenn D. Boreman
  • Vol. 44, Iss. 35 — Dec. 10, 2005
  • pp: 7595–7601

High-order cumulant-based blind deconvolution of Raman spectra

Jinghe Yuan, Ziqiang Hu, and Jinzuo Sun  »View Author Affiliations


Applied Optics, Vol. 44, Issue 35, pp. 7595-7601 (2005)
http://dx.doi.org/10.1364/AO.44.007595


View Full Text Article

Enhanced HTML    Acrobat PDF (168 KB)





Browse Journals / Lookup Meetings

Browse by Journal and Year


   


Lookup Conference Papers

Close Browse Journals / Lookup Meetings

Article Tools

Share
Citations

Abstract

The spectra recorded by a dispersion spectrophotometer are usually distorted by the response function of the instrument. To improve the resolving power, double or triple cascade spectrophotometers with narrow slits have been employed, but the total flux of the radiation available decreases accordingly, resulting in a low signal-to-noise ratio and a longer measuring time. The actual spectra can be restored approximately by mathematically removing the effects of the measuring instruments. Based on the Shalvi–Weinstein criterion, a (6, 2)-order normalized cumulant-based blind deconvolution algorithm for Raman spectral data is proposed. The actual spectral data and the unit-impulse response of the measuring instruments can be estimated simultaneously. By conducting experiments on real Raman spectra of some organic compounds, it is shown that this algorithm has a robust performance and fast convergence behavior and can improve the resolving power and correct the relative intensity distortion considerably.

© 2005 Optical Society of America

OCIS Codes
(300.6170) Spectroscopy : Spectra
(300.6320) Spectroscopy : Spectroscopy, high-resolution
(300.6450) Spectroscopy : Spectroscopy, Raman

ToC Category:
Spectroscopy

History
Original Manuscript: March 17, 2005
Revised Manuscript: August 10, 2005
Manuscript Accepted: August 10, 2005
Published: December 10, 2005

Citation
Jinghe Yuan, Ziqiang Hu, and Jinzuo Sun, "High-order cumulant-based blind deconvolution of Raman spectra," Appl. Opt. 44, 7595-7601 (2005)
http://www.opticsinfobase.org/ao/abstract.cfm?URI=ao-44-35-7595


Sort:  Author  |  Year  |  Journal  |  Reset  

References

  1. Y. Senga, K. Minami, S. Kawata, S. Minami, “Estimation of spectral slit width and blind deconvolution of spectroscopic data by homomorphic filtering,” Appl. Opt. 23, 1601–1608 (1984). [CrossRef] [PubMed]
  2. S. X. Zheng, Laser Raman Spectroscopy (Shanghai Scientific & Technical Publishers, 1985).
  3. C. W. Helstrom, “Image restoration by the method of least squares,” J. Opt. Soc. Am. 57, 297–303 (1967). [CrossRef]
  4. P. A. Jansson, Deconvolution with Application in Spectroscopy (Academic, 1981).
  5. O. Shalvi, E. Weinstein, “Universal methods for blind deconvolution,” in Blind Deconvolution, S. Haykin, ed. (Prentice-Hall, 1994), pp. 122–168.
  6. C. Feng, C. Chi, “Performance of cumulant-based inverse filters for blind deconvolution,” IEEE Trans. Signal Process. 47, 1922–1935 (1999). [CrossRef]
  7. M. Gu, L. Tong, “Domains of attraction of Shalvi–Weinstein receivers,” IEEE Trans. Signal Process. 49, 1397–1408 (2001). [CrossRef]
  8. P. Schniter, L. Tong, “Existence and performance of Shalvi–Weinstein estimators,” IEEE Trans. Signal Process. 49, 2031–2041 (2001). [CrossRef]
  9. A. Mansour, A. K. Barros, N. Ohnishi, “Comparison among three estimators for high order statistics,” presented at the Fifth International Conference on Neural Information Processing, Kitakyushu, Japan, 21–23 October 1998.
  10. J. A. Cadzow, “Blind deconvolution via cumulant extrema,” IEEE Signal Process. Mag. 13, 24–42 (1996). [CrossRef]
  11. X. Zhang, “High-order statistical analysis,” in Modern Signal Processing, 2nd ed., X. Zhang, ed. (Tsinghua University Press, 2003), pp. 263–348.

Cited By

Alert me when this paper is cited

OSA is able to provide readers links to articles that cite this paper by participating in CrossRef's Cited-By Linking service. CrossRef includes content from more than 3000 publishers and societies. In addition to listing OSA journal articles that cite this paper, citing articles from other participating publishers will also be listed.

Figures

Fig. 1 Fig. 2 Fig. 3
 

« Previous Article  |  Next Article »

OSA is a member of CrossRef.

CrossCheck Deposited