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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...
Autores principales: | , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Optical Society of America
2020
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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 |
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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 |