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Related Experiment Video

Updated: May 16, 2026

Direct Comparison of Hyperspectral Stimulated Raman Scattering and Coherent Anti-Stokes Raman Scattering Microscopy for Chemical Imaging

Direct Comparison of Hyperspectral Stimulated Raman Scattering and Coherent Anti-Stokes Raman Scattering Microscopy for Chemical Imaging

Published on: April 28, 2022

Automated cosmic spike filter optimized for process Raman spectroscopy.

Sergey Mozharov¹, Alison Nordon, David Littlejohn

¹Applied Physics Laboratory, University of Washington, Seattle, 98105, USA. sergey@apl.uw.edu

Applied Spectroscopy

|November 14, 2012

Summary

A new automated method accurately detects cosmic spikes in process Raman spectroscopy data. This approach overcomes limitations of existing techniques, offering reliable spike removal without user-defined parameters.

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Multiplex Chemical Imaging Based on Broadband Stimulated Raman Scattering Microscopy

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Published on: July 25, 2022

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Last Updated: May 16, 2026

Direct Comparison of Hyperspectral Stimulated Raman Scattering and Coherent Anti-Stokes Raman Scattering Microscopy for Chemical Imaging

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Published on: April 28, 2022

Multiplex Chemical Imaging Based on Broadband Stimulated Raman Scattering Microscopy

Multiplex Chemical Imaging Based on Broadband Stimulated Raman Scattering Microscopy

Published on: July 25, 2022

Area of Science:

Analytical Chemistry
Spectroscopy

Background:

Cosmic spikes are artifacts in Raman data that require removal.
Existing spike removal methods are often unsuitable for process Raman spectroscopy due to time, accuracy, or parameter-dependency issues.

Purpose of the Study:

To develop and validate a novel, automated method for detecting cosmic spikes in process Raman spectroscopy data.

Main Methods:

A multistage spike recognition algorithm was developed.
The algorithm tracks sharp intensity changes in the time domain.
It distinguishes cosmic spikes from spectral noise and Raman peak variations.

Main Results:

The novel method accurately detects both high and low intensity cosmic spikes.
It effectively differentiates spikes from other spectral features.
The procedure is free from user-defined parameters and operates automatically.

Conclusions:

The developed method provides a reliable and automated solution for cosmic spike removal in process Raman spectroscopy.
It overcomes the limitations of existing algorithms, enhancing data analysis efficiency and accuracy.