SNR enhancement in brillouin microspectroscopy using spectrum reconstruction

Yuchen Xiang, Matthew R. Foreman, Peter Török*

*Corresponding author for this work

Research output: Contribution to journalArticlepeer-review

12 Citations (Scopus)

Abstract

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.

Original languageEnglish
Pages (from-to)1020-1031
Number of pages12
JournalBiomedical Optics Express
Volume11
Issue number2
DOIs
Publication statusPublished - Feb 1 2020
Externally publishedYes

Bibliographical note

Publisher Copyright:
© 2020 OSA - The Optical Society. All rights reserved.

ASJC Scopus Subject Areas

  • Biotechnology
  • Atomic and Molecular Physics, and Optics

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