Masia, Francesco  ORCID: https://orcid.org/0000-0003-4958-410X, Karuna, Arnica, Borri, Paola ORCID: https://orcid.org/0000-0002-7873-3314 and Langbein, Wolfgang Werner ORCID: https://orcid.org/0000-0001-9786-1023
2015.
Hyperspectral image analysis for CARS, SRS, and Raman data.
Journal of Raman Spectroscopy
46
(8)
, pp. 727-734.
10.1002/jrs.4729
|
Preview |
PDF
- Published Version
Available under License Creative Commons Attribution. Download (3MB) | Preview |
Abstract
In this work, we have significantly enhanced the capabilities of the hyperspectral image analysis (HIA) first developed by Masia et al. [1] The HIA introduced a method to factorize the hyperspectral data into the product of component concentrations and spectra for quantitative analysis of the chemical composition of the sample. The enhancements shown here comprise (1) a spatial weighting to reduce the spatial variation of the spectral error, which improves the retrieval of the chemical components with significant local but small global concentrations; (2) a new selection criterion for the spectra used when applying sparse sampling[2] to speed up sequential hyperspectral imaging; and (3) a filter for outliers in the data using singular value decomposition, suited e.g. to suppress motion artifacts. We demonstrate the enhancements on coherent anti-Stokes Raman scattering, stimulated Raman scattering, and spontaneous Raman data. We provide the HIA software as executable for public use.
| Item Type: | Article |
|---|---|
| Date Type: | Publication |
| Status: | Published |
| Schools: | Schools > Biosciences Schools > Physics and Astronomy |
| Subjects: | Q Science > QC Physics |
| Uncontrolled Keywords: | coherent Raman micro-spectroscopy; hyperspectral image analysis; sparse sampling |
| Publisher: | Wiley-Blackwell |
| ISSN: | 0377-0486 |
| Funders: | EPSRC, BBSRC |
| Date of First Compliant Deposit: | 30 March 2016 |
| Date of Acceptance: | 5 May 2015 |
| Last Modified: | 09 May 2023 00:25 |
| URI: | https://orca.cardiff.ac.uk/id/eprint/74543 |
Citation Data
Cited 34 times in Scopus. View in Scopus. Powered By Scopus® Data
Actions (repository staff only)
 |
Edit Item |
Dimensions
Dimensions