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Vector casting for noise reduction
Author(s) -
Gebrekidan Medhanie Tesfay,
Knipfer Christian,
Braeuer Andreas Siegfried
Publication year - 2020
Publication title -
journal of raman spectroscopy
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.748
H-Index - 110
eISSN - 1097-4555
pISSN - 0377-0486
DOI - 10.1002/jrs.5835
Subject(s) - noise reduction , binary golay code , noise (video) , wavelet , reduction (mathematics) , algorithm , raman spectroscopy , signal (programming language) , signal to noise ratio (imaging) , computer science , acoustics , pattern recognition (psychology) , mathematics , artificial intelligence , physics , optics , telecommunications , geometry , image (mathematics) , programming language
We report a new method for the reduction of noise from spectra. This method is based on casting vectors from one data point to the following data points of the noisy spectrum. The noise‐reduced spectrum is computed from the casted vectors within a margin that is identified by an envelope‐finder algorithm. We compared here the presented method with the Savitzky–Golay and the wavelet transform approaches for noise reduction using simulated Raman spectra of various signal‐to‐noise ratios between 1 and 25 dB and experimentally acquired Raman spectra. The method presented here performs well compared with the Savitzky–Golay and the wavelets‐based denoising method, especially at small signal‐to‐noise ratios and furthermore relies on a minimum of human input requirements.