Literature DB >> 26688879

Joint baseline-correction and denoising for Raman spectra.

Hai Liu1, Zhaoli Zhang, Sanya Liu, Luxin Yan, Tingting Liu, Tianxu Zhang.   

Abstract

Laser instruments often suffer from the problem of baseline drift and random noise, which greatly degrade spectral quality. In this article, we propose a variation model that combines baseline correction and denoising. First, to guide the baseline estimation, morphological operations are adopted to extract the characteristics of the degraded spectrum. Second, to suppress noise in both the spectrum and baseline, Tikhonov regularization is introduced. Moreover, we describe an efficient optimization scheme that alternates between the latent spectrum estimation and the baseline correction until convergence. The major novel aspect of the proposed algorithms is the estimation of a smooth spectrum and removal of the baseline simultaneously. Results of a comparison with state-of-the-art methods demonstrate that the proposed method outperforms them in both qualitative and quantitative assessments.

Year:  2015        PMID: 26688879     DOI: 10.1366/14-07760

Source DB:  PubMed          Journal:  Appl Spectrosc        ISSN: 0003-7028            Impact factor:   2.388


  3 in total

1.  A general-purpose signal processing algorithm for biological profiles using only first-order derivative information.

Authors:  Yuanjie Liu; Jianhan Lin
Journal:  BMC Bioinformatics       Date:  2019-11-27       Impact factor: 3.169

2.  Deep Learning for Reconstructing Low-Quality FTIR and Raman Spectra─A Case Study in Microplastic Analyses.

Authors:  Josef Brandt; Karin Mattsson; Martin Hassellöv
Journal:  Anal Chem       Date:  2021-11-22       Impact factor: 6.986

3.  Raman Spectroscopy-Based Measurements of Single-Cell Phenotypic Diversity in Microbial Populations.

Authors:  Cristina García-Timermans; Ruben Props; Boris Zacchetti; Myrsini Sakarika; Frank Delvigne; Nico Boon
Journal:  mSphere       Date:  2020-10-28       Impact factor: 4.389

  3 in total

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