Vector casting for noise reduction

2020/01/23 by Medhanie Tesfay Gebrekidan, Christian Knipfer, Andreas Braeuer +1 · 1 citation
Biochemistry, Genetics and Molecular Biology · Chemistry · Computer Science · #Image and Signal Denoising Methods #Spectroscopy Techniques in Biomedical and Chemical Research #Spectroscopy and Chemometric Analyses

paper · pdf · doi:10.1002/jrs.5835

openalex publication_date 2020/01/23 · openalex created_date 2025/10/10 · openalex updated_date 2026/07/30

Abstract

Abstract 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.

Citations

• A shifted‐excitation Raman difference spectroscopy (SERDS) evaluation strategy for the efficient isolation of Raman spectra from extreme fluorescence interference
• Smoothing and Differentiation of Data by Simplified Least Squares Procedures.

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• Refinement of spectra using a deep neural network: Fully automated removal of noise and background

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