Iterative mollifier‐based despiking of the single‐scan Raman spectra
Removing cosmic spikes from experimental Raman spectra is highly important for the processing of big datasets. The despiking approaches are at present under active development. Herein, an algorithm is described that can handle the single‐scan spectra and works efficiently for both regular and apodiz...
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| Published in | Journal of Raman spectroscopy Vol. 53; no. 2; pp. 256 - 259 |
|---|---|
| Main Author | |
| Format | Journal Article |
| Language | English |
| Published |
Bognor Regis
Wiley Subscription Services, Inc
01.02.2022
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| Subjects | |
| Online Access | Get full text |
| ISSN | 0377-0486 1097-4555 |
| DOI | 10.1002/jrs.6277 |
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| Abstract | Removing cosmic spikes from experimental Raman spectra is highly important for the processing of big datasets. The despiking approaches are at present under active development. Herein, an algorithm is described that can handle the single‐scan spectra and works efficiently for both regular and apodized spectra. It is based on an iterative detection–fitting–subtraction cycle, in which the detection is based on a mollification operation. The approach does not require setting arbitrary threshold parameters for the detection. The efficiency of the algorithm is compared with the state‐of‐the‐art approaches. It is shown that it can remove the spikes at which fails the built‐in device software. The Python code is provided.
Mollifier‐based algorithm can detect and subtract even minor spikes missed by the built‐in device software. |
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| AbstractList | Removing cosmic spikes from experimental Raman spectra is highly important for the processing of big datasets. The despiking approaches are at present under active development. Herein, an algorithm is described that can handle the single‐scan spectra and works efficiently for both regular and apodized spectra. It is based on an iterative detection–fitting–subtraction cycle, in which the detection is based on a mollification operation. The approach does not require setting arbitrary threshold parameters for the detection. The efficiency of the algorithm is compared with the state‐of‐the‐art approaches. It is shown that it can remove the spikes at which fails the built‐in device software. The Python code is provided. Removing cosmic spikes from experimental Raman spectra is highly important for the processing of big datasets. The despiking approaches are at present under active development. Herein, an algorithm is described that can handle the single‐scan spectra and works efficiently for both regular and apodized spectra. It is based on an iterative detection–fitting–subtraction cycle, in which the detection is based on a mollification operation. The approach does not require setting arbitrary threshold parameters for the detection. The efficiency of the algorithm is compared with the state‐of‐the‐art approaches. It is shown that it can remove the spikes at which fails the built‐in device software. The Python code is provided. Mollifier‐based algorithm can detect and subtract even minor spikes missed by the built‐in device software. |
| Author | Korepanov, Vitaly |
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| References | 2020; 7 2018; 2018 2019; 73 2017; 48 2020; 74 2018; 179 2002; 33 1998 2016; 155 2016; 71 2007; 61 1992; 64 2012; 66 1938; 4 2001; 446 e_1_2_7_6_1 e_1_2_7_5_1 e_1_2_7_4_1 e_1_2_7_3_1 e_1_2_7_9_1 e_1_2_7_8_1 e_1_2_7_7_1 e_1_2_7_18_1 e_1_2_7_17_1 e_1_2_7_16_1 e_1_2_7_2_1 e_1_2_7_14_1 e_1_2_7_12_1 Beebe Kenneth R. (e_1_2_7_13_1) 1998 e_1_2_7_11_1 e_1_2_7_10_1 Soboleff S. (e_1_2_7_15_1) 1938; 4 |
| References_xml | – volume: 155 start-page: 1 year: 2016 publication-title: Chemom. Intel. Lab. Syst. – volume: 73 start-page: 1019 year: 2019 publication-title: Appl. Spectrosc. – volume: 2018 start-page: 2674 issue: 143 year: 2018 publication-title: Analyst – volume: 446 start-page: 71 year: 2001 publication-title: Anal. Chim. Acta – volume: 7 year: 2020 publication-title: MethodsX – volume: 66 start-page: 1326 year: 2012 publication-title: Appl. Spectrosc. – volume: 61 start-page: 1015 year: 2007 publication-title: Appl. Spectrosc. – volume: 64 start-page: 2575 year: 1992 publication-title: Anal. Chem. – volume: 179 start-page: 82 year: 2018 publication-title: Chemom. Intel. Lab. Syst. – volume: 33 start-page: 599 year: 2002 publication-title: J. Raman Spectrosc. – volume: 4 start-page: 471 year: 1938 publication-title: Recueil Math. Nouvelle Sér. – volume: 73 start-page: 893 year: 2019 publication-title: Appl. Spectrosc. – volume: 48 start-page: 336 year: 2017 publication-title: J. Raman Spectrosc. – volume: 74 start-page: 427 year: 2020 publication-title: Appl. Spectrosc. – volume: 71 start-page: 507 issue: 3 year: 2016 publication-title: Appl. Spectrosc. – year: 1998 – ident: e_1_2_7_4_1 doi: 10.1366/000370207781745847 – ident: e_1_2_7_16_1 doi: 10.1002/jrs.5010 – ident: e_1_2_7_12_1 doi: 10.1002/jrs.885 – ident: e_1_2_7_11_1 doi: 10.1016/j.chemolab.2016.03.024 – ident: e_1_2_7_14_1 doi: 10.1366/12-06660 – ident: e_1_2_7_9_1 doi: 10.1021/ac00045a019 – volume: 4 start-page: 471 year: 1938 ident: e_1_2_7_15_1 publication-title: Recueil Math. Nouvelle Sér. – ident: e_1_2_7_5_1 doi: 10.1016/j.chemolab.2018.06.009 – ident: e_1_2_7_6_1 doi: 10.1177/0003702819850584 – ident: e_1_2_7_7_1 doi: 10.1016/j.mex.2020.100883 – ident: e_1_2_7_2_1 doi: 10.1177/0003702816668528 – ident: e_1_2_7_17_1 doi: 10.1039/C8AN00710A – ident: e_1_2_7_18_1 – ident: e_1_2_7_3_1 doi: 10.1016/s0003-2670(01)01267-3 – ident: e_1_2_7_8_1 doi: 10.1177/0003702819888949 – ident: e_1_2_7_10_1 doi: 10.1177/0003702819839098 – volume-title: Chemometrics: a practical guide year: 1998 ident: e_1_2_7_13_1 |
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| Title | Iterative mollifier‐based despiking of the single‐scan Raman spectra |
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