A DATA FUSION METHOD FOR THE DELAYERING OF X-RAY FLUORESCENCE IMAGES OF PAINTED WORKS OF ART

L. D. Fiske*, A. K. Katsaggelos, M. C.G. Aalders, M. Alfeld, Marc Sebastian Walton, O. Cossairt

*Corresponding author for this work

Research output: Chapter in Book/Report/Conference proceedingConference contribution

1 Scopus citations

Abstract

In this manuscript, we address the problem of studying layer structure in X-ray Fluorescence (XRF) elemental maps of paintings through the incorporation of reflectance imaging spectral data in the visible or near IR range. We propose a conceptually flexible approach, which involves an initial clustering step for the visible hyperspectral reflectance data (RIS) and the formation of a synthetic surface XRF image. Considering the difference of the full and synthetic surface XRF images, surface and subsurface correlated features are then identified. Results are demonstrated on real and simulated data.

Original languageEnglish (US)
Title of host publication2021 IEEE International Conference on Image Processing, ICIP 2021 - Proceedings
PublisherIEEE Computer Society
Pages3458-3462
Number of pages5
ISBN (Electronic)9781665441155
DOIs
StatePublished - 2021
Event2021 IEEE International Conference on Image Processing, ICIP 2021 - Anchorage, United States
Duration: Sep 19 2021Sep 22 2021

Publication series

NameProceedings - International Conference on Image Processing, ICIP
Volume2021-September
ISSN (Print)1522-4880

Conference

Conference2021 IEEE International Conference on Image Processing, ICIP 2021
Country/TerritoryUnited States
CityAnchorage
Period9/19/219/22/21

Keywords

  • Cultural heritage science
  • Data fusion
  • Hyperspectral imaging
  • RIS
  • XRF

ASJC Scopus subject areas

  • Software
  • Computer Vision and Pattern Recognition
  • Signal Processing

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