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Multiframe-based non-local means denoising for Raman spectra

Multiframe-based non-local means denoising for Raman spectra
Multiframe-based non-local means denoising for Raman spectra
A method for denoising Raman spectra is presented in this paper. The approach is based on the principle that the original signal can be restored by averaging pixels based on structure similarity. Similarity searching and averaging are not limited to the neighbouring pixels but extended throughout the entire signal range across different frames. This approach is distinguished from the conventional single-frame neighbour pixel-based filtering. The effectiveness and robustness of the proposed method are demonstrated through denoising simulated and experimental Raman data sets with fixed denoising parameters. Several denoised results and statistical indicators are presented for the simulated data. Recovery of the experimental Raman spectrum from our newly developed cost-effective waveguide-enhanced Raman spectroscopy system is also presented and compared to the spectrum from a conventional expensive Raman microscope for the same analyte.
Multi-frame denoising, Non-local means, Spectra restoration, Waveguide enhanced Raman spectroscopy
1386-1425
Liu, Zhen
ab2e4170-b059-48c1-8ac7-63ee8b8f10b3
Ettabib, Mohamed A.
71b98cd3-9b2a-4f73-b4c2-0f4b59cacf50
Bowden, Bethany M.
084eeee9-0c23-4d40-ab63-afd7574711fb
Bartlett, Philip N.
d99446db-a59d-4f89-96eb-f64b5d8bb075
Wilkinson, James S.
73483cf3-d9f2-4688-9b09-1c84257884ca
Zervas, Michael N.
1840a474-dd50-4a55-ab74-6f086aa3f701
Liu, Zhen
ab2e4170-b059-48c1-8ac7-63ee8b8f10b3
Ettabib, Mohamed A.
71b98cd3-9b2a-4f73-b4c2-0f4b59cacf50
Bowden, Bethany M.
084eeee9-0c23-4d40-ab63-afd7574711fb
Bartlett, Philip N.
d99446db-a59d-4f89-96eb-f64b5d8bb075
Wilkinson, James S.
73483cf3-d9f2-4688-9b09-1c84257884ca
Zervas, Michael N.
1840a474-dd50-4a55-ab74-6f086aa3f701

Liu, Zhen, Ettabib, Mohamed A., Bowden, Bethany M., Bartlett, Philip N., Wilkinson, James S. and Zervas, Michael N. (2024) Multiframe-based non-local means denoising for Raman spectra. Spectrochimica Acta Part A Molecular and Biomolecular Spectroscopy, 310, [123931]. (doi:10.1016/j.saa.2024.123931).

Record type: Article

Abstract

A method for denoising Raman spectra is presented in this paper. The approach is based on the principle that the original signal can be restored by averaging pixels based on structure similarity. Similarity searching and averaging are not limited to the neighbouring pixels but extended throughout the entire signal range across different frames. This approach is distinguished from the conventional single-frame neighbour pixel-based filtering. The effectiveness and robustness of the proposed method are demonstrated through denoising simulated and experimental Raman data sets with fixed denoising parameters. Several denoised results and statistical indicators are presented for the simulated data. Recovery of the experimental Raman spectrum from our newly developed cost-effective waveguide-enhanced Raman spectroscopy system is also presented and compared to the spectrum from a conventional expensive Raman microscope for the same analyte.

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Accepted/In Press date: 19 January 2024
e-pub ahead of print date: 20 January 2024
Published date: 5 April 2024
Additional Information: Publisher Copyright: © 2024 The Authors
Keywords: Multi-frame denoising, Non-local means, Spectra restoration, Waveguide enhanced Raman spectroscopy

Identifiers

Local EPrints ID: 477805
URI: http://eprints.soton.ac.uk/id/eprint/477805
ISSN: 1386-1425
PURE UUID: b162a656-841d-4c27-8e6d-2834380d37ee
ORCID for Bethany M. Bowden: ORCID iD orcid.org/0000-0002-2312-2727
ORCID for Philip N. Bartlett: ORCID iD orcid.org/0000-0002-7300-6900
ORCID for James S. Wilkinson: ORCID iD orcid.org/0000-0003-4712-1697
ORCID for Michael N. Zervas: ORCID iD orcid.org/0000-0002-0651-4059

Catalogue record

Date deposited: 14 Jun 2023 16:53
Last modified: 30 Aug 2024 01:56

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Contributors

Author: Zhen Liu
Author: Mohamed A. Ettabib
Author: Bethany M. Bowden ORCID iD
Author: Michael N. Zervas ORCID iD

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