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- Title
Alternating direction method of multipliers for linear hyperspectral unmixing.
- Authors
Dai, Yu-Hong; Xu, Fangfang; Zhang, Liwei
- Abstract
Linear hyperspectral unmixing (LHU) is a class of important problems in remote sensing. It can be modelled by a linearly constrained convex optimization problem with a coupled objective function. This paper proposes an alternating direction method of multipliers (ADMM) for solving this LHU model. The special structure of the LHU model allows explicit solutions to the subproblems in the ADMM and hence the ADMM is easily implementable. The global convergence of the ADMM is established despite the existence of a coupled term in the objective function. Our numerical experiments with four data sets demonstrated that the proposed ADMM is effective for solving the LHU model.
- Subjects
REMOTE sensing; MULTIPLIERS (Mathematical analysis); CONSTRAINED optimization
- Publication
Mathematical Methods of Operations Research, 2023, Vol 97, Issue 3, p289
- ISSN
1432-2994
- Publication type
Article
- DOI
10.1007/s00186-023-00815-2