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Multivariate analysis on fused hyperspectral datasets within Cultural Heritage field

Authors :
Di Benedetto Alessia
de Almieda Nieto Luìs Manuel
Candeo Alessia
Valentini Gianluca
Comelli Daniela
Alfeld Matthias
Source :
EPJ Web of Conferences, Vol 309, p 14007 (2024)
Publication Year :
2024
Publisher :
EDP Sciences, 2024.

Abstract

This work introduces a novel method to multivariate analysis applied to fused hyperspectral datasets in the field of Cultural Heritage (CH). Hyperspectral Imaging is a well-established approach for the non-invasive examination of artworks, offering insights into their composition and conservation status. In CH field, a combination of hyperspectral techniques is usually employed to reach a comprehensive understanding of the artwork. To deal with hyperspectral data, multivariate statistical methods are essential due to the complexity of the data. The process involves factorizing the data matrix to highlight components and reduce dimensionality, with techniques such as Non-negative Matrix Factorization (NMF) gaining prominence. To maximize the synergies between multimodal datasets, the fusion of hyperspectral datasets can be coupled with multivariate analysis, with potential applications in CH. In this work, I will show examples of this approach with different combinations of datasets, including reflectance and transmittance spectral imaging, Fluorescence Lifetime Imaging and Time-Gated Hyperspectral Imaging, and Raman and fluorescence spectroscopy micro-mapping.

Subjects

Subjects :
Physics
QC1-999

Details

Language :
English
ISSN :
2100014X and 49447491
Volume :
309
Database :
Directory of Open Access Journals
Journal :
EPJ Web of Conferences
Publication Type :
Academic Journal
Accession number :
edsdoj.461c64d6ad49447491b53725db0f8eb8
Document Type :
article
Full Text :
https://doi.org/10.1051/epjconf/202430914007