Publication
Title
A multisensor hyperspectral benchmark dataset for unmixing of intimate mixtures
Author
Abstract
Optical hyperspectral cameras capture the spectral reflectance of materials. Since many materials behave as heterogeneous intimate mixtures with which each photon interacts differently, the relationship between spectral reflectance and material composition is very complex. Quantitative validation of spectral unmixing algorithms requires high-quality ground truth fractional abundance data, which are very difficult to obtain. In this work, we generated a comprehensive laboratory ground truth dataset of intimately mixed mineral powders. For this, five clay powders (Kaolin, Roof clay, Red clay, mixed clay, and Calcium hydroxide) were mixed homogeneously to prepare 325 samples of 60 binary, 150 ternary, 100 quaternary, and 15 quinary mixtures. Thirteen different hyperspectral sensors have been used to acquire the reflectance spectra of these mixtures in the visible, near, short, mid, and long-wavelength infrared regions (350-15385) nm. Overlaps in wavelength regions due to the operational ranges of each sensor and variations in acquisition conditions resulted in a large amount of spectral variability. Ground truth composition is given by construction, but to verify that the generated samples are sufficiently homogeneous, XRD and XRF elemental analysis is performed. We believe these data will be beneficial for validating advanced methods for nonlinear unmixing and material composition estimation, including studying spectral variability and training supervised unmixing approaches. The datasets can be downloaded from the following link: https://github.com/VisionlabHyperspectral/Multisensor_datasets.
Language
English
Source (journal)
IEEE sensors journal / Institute of Electrical and Electronics Engineers [New York, N.Y.] - New York, N.Y., 2001, currens
Publication
New York, N.Y. : IEEE Sensors Council , 2024
ISSN
1530-437X [print]
1558-1748 [online]
DOI
10.1109/JSEN.2023.3343552
Volume/pages
24 :4 (2024) , p. 4694-4710
ISI
001173599400063
Full text (Publisher's DOI)
Full text (open access)
The author-created version that incorporates referee comments and is the accepted for publication version Available from 28.06.2024
Full text (publisher's version - intranet only)
UAntwerpen
Faculty/Department
Research group
Project info
Material inspection by shortwave infrared hyperspectral image analysis.
Advanced hyperspectral image analysis for material characterization.
Publication type
Subject
Affiliation
Publications with a UAntwerp address
External links
Record
Identifier
Creation 15.02.2024
Last edited 02.04.2024
To cite this reference