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. 2020 Mar 25;10:5699. doi: 10.1038/s41598-020-62740-2

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© The Author(s) 2020

Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The images or other third party material in this article are included in the article’s Creative Commons license, unless indicated otherwise in a credit line to the material. If material is not included in the article’s Creative Commons license and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this license, visit http://creativecommons.org/licenses/by/4.0/.

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A comparison of spectral denoising techniques as measured by SNR gain (normalized to SNR of the input noisy data) and SD (presented as 100%-SD) for two different pixel sizes representing HD and standard definition imaging magnifications. Five methods were tested: Savitzky-Golay (SG), Fourier transform (FT), Principal Component Analysis (PCA), Minimum Noise Fraction (MNF) and spectral wavelets (Wavelets). The size of the dots corresponds to the initial noise level, starting with the highest noise for the largest dot (2 scans) and going down to the smallest (256 scans). The optimal parameters for each of the methods and noise levels are given in Supplementary Materials.