Publication
Title
A supervised approach for estimating fractional abundances of binary intimate mixtures
Author
Abstract
In this work, we propose a supervised framework for spectral unmixing of binary intimate mixtures. The core idea is based on geodesic distance measurements and regression to estimate the fractional abundances. The main assumption is that spectral reflectances of binary mixtures form a curve between the two endmembers, and the mixture's relative position on this curve serves as an indicator of its fractional abundances. We propose four novel approaches to approximate this relative position. From this, the fractional abundances are obtained using Gaussian process regression. The proposed framework simultaneously copes with the spectral variability by hypersphere and high-dimensional simplex projections. The approach is extensively validated on real datasets, including binary mineral mixtures and industrial clay powder mixtures produced in a laboratory setting, comprising 60 binary mixtures derived from five types of clay powders: Kaolin, Roof clay, Red clay, mixed clay, and Calcium hydroxide, measured by a variety of hyperspectral sensors in the VNIR-SWIR and mid-and longwave infrared regions. A comparison with the linear mixing model and several nonlinear mixing models demonstrates the superiority of the proposed approach.
Language
English
Source (journal)
IEEE journal of selected topics in applied earth observation and remote sensing / IEEE geoscience and remote sensing society; IEEE committee on earth observations. - New York (N.Y.)
Publication
New York (N.Y.) : IEEE , 2024
ISSN
1939-1404
DOI
10.1109/JSTARS.2024.3387750
Volume/pages
(2024) , p. 1-11
Full text (Publisher's DOI)
Full text (open access)
UAntwerpen
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Research group
Publication type
Subject
Affiliation
Publications with a UAntwerp address
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Record
Identifier
Creation 15.04.2024
Last edited 18.04.2024
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