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Raman Spectral Data De-noising based on Wavelet Analysis

by Nitendra Kumar, A. H. Siddiqi, Khursheed Alam
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International Journal of Computer Applications
Foundation of Computer Science (FCS), NY, USA
Volume 102 - Number 16
Year of Publication: 2014
Authors: Nitendra Kumar, A. H. Siddiqi, Khursheed Alam
10.5120/17899-8864

Nitendra Kumar, A. H. Siddiqi, Khursheed Alam . Raman Spectral Data De-noising based on Wavelet Analysis. International Journal of Computer Applications. 102, 16 ( September 2014), 20-22. DOI=10.5120/17899-8864

@article{ 10.5120/17899-8864,
author = { Nitendra Kumar, A. H. Siddiqi, Khursheed Alam },
title = { Raman Spectral Data De-noising based on Wavelet Analysis },
journal = { International Journal of Computer Applications },
issue_date = { September 2014 },
volume = { 102 },
number = { 16 },
month = { September },
year = { 2014 },
issn = { 0975-8887 },
pages = { 20-22 },
numpages = {9},
url = { https://ijcaonline.org/archives/volume102/number16/17899-8864/ },
doi = { 10.5120/17899-8864 },
publisher = {Foundation of Computer Science (FCS), NY, USA},
address = {New York, USA}
}
%0 Journal Article
%1 2024-02-06T22:33:16.767517+05:30
%A Nitendra Kumar
%A A. H. Siddiqi
%A Khursheed Alam
%T Raman Spectral Data De-noising based on Wavelet Analysis
%J International Journal of Computer Applications
%@ 0975-8887
%V 102
%N 16
%P 20-22
%D 2014
%I Foundation of Computer Science (FCS), NY, USA
Abstract

Nowadays, most analytical instruments in modern laboratories are computerized, partly owing to the rapid development of advanced micro-electronic technology. Digitalized spectroscopic data can be exported from these instruments very easily for subsequent signal processing. Raman Spectroscopy is widely recognized as powerful, non-destructive techniques for characterizing materials. The key to realize the qualitative and quantitative analysis is data processing and analysis. But signals in Raman spectral analysis often have noise, which greatly influences the achievement of accurate analytical results. The de-noising of Raman spectral is an important part of de-noising. Wavelet functions are localized both time and frequency (or scale) and in time, via dilations and translations of the mother wavelet, respectively, both time and frequency information are maintained after transformation. This paper presents wavelet based de-noising method for Raman Spectral data of Sr2+ modified PMN-PZT and compared the results with Daubechies, Coiflet, Symlet.

References
  1. Chen. S. , Lin X. , Yuen C. , Padmanabhan S, Beuerman Roger W. and Liu Q, 2014, Recovery of Raman Spectra with low signal-to-noise ratio using Wiener estimation, Optical Society of America. Vol. 22. No. 10.
  2. Raman C. V. , 1928, "A new type of secondary radiation", Nature, 121, 619.
  3. Yang Y, Guo L. and Li F. , 2011, "Application of wavelet transform in spectral data de-noising", 978-1-0246-4/11, IEEE.
  4. Gang F. , 2008, "Noise removal of Raman spectra using interval thresholding method", DOI 0. 1109/IITA, 573, IEEE.
  5. Chen C. , Peng F. , Cheng Q and Xu D. , 2009, "Application of Wavelet Packet Transform to Compressing Raman Spectra Data", Proc. of SPIE Vol. 7280 728009-1.
  6. Ehrentreich F. , Summchen F, 2001, "Spike removal and De-noising of Raman spectra by wavelet transform methods", Analytical chemistry, Vol. 73, no. 17, pp. 4364-4373.
  7. Cai W. , Wang L. , Pan Z, Zuo Z. , Xu C. , Shao, 2001, "Application of the Wavelet of Raman spectra", Journal of Raman Spectroscopy, Vol. 32, No. 3, pp. 207-209.
  8. Silveria Jr. L. , Benito B. ,. Amaro Z. R and Tadeu T. P. M. , 2010, "Discrete wavelet transform for de-nosing Raman spectra of human skin tissue used in a discriminate diagnostic algorithm", Journal of Instrumentation science & Technology, 38:268-282, Taylor & Francis, ISSN: 1073-9149.
  9. Ramos, P. M, Ruisa'nchez I. , 2005, "Noise and background removal in Raman spectra of ancient pigments using wavelet transform", J. Raman Spectroscopy, 36(9), 848–856.
  10. Hu Y. , Jiang T. , Shen A. , Li W. , Wang X. , and Hu J. , 2007, "A background elimination method based on wavelet transform for Raman spectra", Chemometer Intell. Lab. Syst, 85(1), 94-101.
  11. Kumar A. and Mishra S. K. , 2014, Effects of Sr2+ substitution on structural, dielectric and piezoelectric properties of PZT-PMN ceramic. Int. J. Miner. Metall. Mater, (Feb. 2014), Vol. 21, No. 2.
Index Terms

Computer Science
Information Sciences

Keywords

Raman Spectral Signal Wavelet Analysis Signal De-noising

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