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Main Authors: Foix-Colonier, Nils, Bourguignon, Sébastien
Format: Preprint
Published: 2025
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Online Access:https://arxiv.org/abs/2512.16432
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author Foix-Colonier, Nils
Bourguignon, Sébastien
author_facet Foix-Colonier, Nils
Bourguignon, Sébastien
contents Linear spectral unmixing under nonnegativity and sum-to-one constraints is a convex optimization problem for which many algorithms were proposed. In practice, especially for supervised unmixing (i.e., with a large dictionary), solutions tend to be sparse due to the nonnegativity of the abundances, thereby motivating the use of an active-set solver. Given the problem specific features, it seems advantageous to design a dedicated algorithm in order to gain computational performance compared to generic solvers. In this paper, we propose to derive such a specific algorithm, while extending the nonnegativity constraints to broader minimum abundance constraints.
format Preprint
id arxiv_https___arxiv_org_abs_2512_16432
institution arXiv
publishDate 2025
record_format arxiv
spellingShingle An active-set algorithm for spectral unmixing
Foix-Colonier, Nils
Bourguignon, Sébastien
Signal Processing
Linear spectral unmixing under nonnegativity and sum-to-one constraints is a convex optimization problem for which many algorithms were proposed. In practice, especially for supervised unmixing (i.e., with a large dictionary), solutions tend to be sparse due to the nonnegativity of the abundances, thereby motivating the use of an active-set solver. Given the problem specific features, it seems advantageous to design a dedicated algorithm in order to gain computational performance compared to generic solvers. In this paper, we propose to derive such a specific algorithm, while extending the nonnegativity constraints to broader minimum abundance constraints.
title An active-set algorithm for spectral unmixing
topic Signal Processing
url https://arxiv.org/abs/2512.16432