Cargando…

SNR enhancement in brillouin microspectroscopy using spectrum reconstruction

Brillouin spectroscopy can suffer from low signal-to-noise ratios (SNRs). Such low SNRs can render common data analysis protocols unreliable, especially for SNRs below ∼10. In this work we exploit two denoising algorithms, namely maximum entropy reconstruction (MER) and wavelet analysis (WA), to imp...

Descripción completa

Detalles Bibliográficos
Autores principales: Xiang, YuChen, Foreman, Matthew R., Török, Peter
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Optical Society of America 2020
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7041457/
https://www.ncbi.nlm.nih.gov/pubmed/32133235
http://dx.doi.org/10.1364/BOE.380798
_version_ 1783501159895400448
author Xiang, YuChen
Foreman, Matthew R.
Török, Peter
author_facet Xiang, YuChen
Foreman, Matthew R.
Török, Peter
author_sort Xiang, YuChen
collection PubMed
description Brillouin spectroscopy can suffer from low signal-to-noise ratios (SNRs). Such low SNRs can render common data analysis protocols unreliable, especially for SNRs below ∼10. In this work we exploit two denoising algorithms, namely maximum entropy reconstruction (MER) and wavelet analysis (WA), to improve the accuracy and precision in determination of Brillouin shifts and linewidth. Algorithm performance is quantified using Monte-Carlo simulations and benchmarked against the Cramér-Rao lower bound. Superior estimation results are demonstrated even at low SNRs (≥ 1). Denoising is furthermore applied to experimental Brillouin spectra of distilled water at room temperature, allowing the speed of sound in water to be extracted. Experimental and theoretical values were found to be consistent to within ±1% at unity SNR.
format Online
Article
Text
id pubmed-7041457
institution National Center for Biotechnology Information
language English
publishDate 2020
publisher Optical Society of America
record_format MEDLINE/PubMed
spelling pubmed-70414572020-03-04 SNR enhancement in brillouin microspectroscopy using spectrum reconstruction Xiang, YuChen Foreman, Matthew R. Török, Peter Biomed Opt Express Article Brillouin spectroscopy can suffer from low signal-to-noise ratios (SNRs). Such low SNRs can render common data analysis protocols unreliable, especially for SNRs below ∼10. In this work we exploit two denoising algorithms, namely maximum entropy reconstruction (MER) and wavelet analysis (WA), to improve the accuracy and precision in determination of Brillouin shifts and linewidth. Algorithm performance is quantified using Monte-Carlo simulations and benchmarked against the Cramér-Rao lower bound. Superior estimation results are demonstrated even at low SNRs (≥ 1). Denoising is furthermore applied to experimental Brillouin spectra of distilled water at room temperature, allowing the speed of sound in water to be extracted. Experimental and theoretical values were found to be consistent to within ±1% at unity SNR. Optical Society of America 2020-01-22 /pmc/articles/PMC7041457/ /pubmed/32133235 http://dx.doi.org/10.1364/BOE.380798 Text en Published by The Optical Society under the terms of the Creative Commons Attribution 4.0 License. Further distribution of this work must maintain attribution to the author(s) and the published article’s title, journal citation, and DOI. Published by The Optical Society under the terms of the Creative Commons Attribution 4.0 License (http://creativecommons.org/licenses/by/4.0/) . Further distribution of this work must maintain attribution to the author(s) and the published article’s title, journal citation, and DOI.
spellingShingle Article
Xiang, YuChen
Foreman, Matthew R.
Török, Peter
SNR enhancement in brillouin microspectroscopy using spectrum reconstruction
title SNR enhancement in brillouin microspectroscopy using spectrum reconstruction
title_full SNR enhancement in brillouin microspectroscopy using spectrum reconstruction
title_fullStr SNR enhancement in brillouin microspectroscopy using spectrum reconstruction
title_full_unstemmed SNR enhancement in brillouin microspectroscopy using spectrum reconstruction
title_short SNR enhancement in brillouin microspectroscopy using spectrum reconstruction
title_sort snr enhancement in brillouin microspectroscopy using spectrum reconstruction
topic Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7041457/
https://www.ncbi.nlm.nih.gov/pubmed/32133235
http://dx.doi.org/10.1364/BOE.380798
work_keys_str_mv AT xiangyuchen snrenhancementinbrillouinmicrospectroscopyusingspectrumreconstruction
AT foremanmatthewr snrenhancementinbrillouinmicrospectroscopyusingspectrumreconstruction
AT torokpeter snrenhancementinbrillouinmicrospectroscopyusingspectrumreconstruction