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- W2547938406 abstract "Several techniques exist for dealing with spectral variability in hyperspectral unmixing, such as multiple endmember spectral mixture analysis (MESMA) or compositional models. These algorithms are computationally very involved, and often cannot be executed on problems of reasonable size. In this work, we present a new algorithm for solving the unmixing problem when spectral variability is present. The algorithm uses a library-based approach to describe the variability present in each class, and executes an alternating optimization with respect to these libraries. The optimization problem itself is constructed as an angle minimization problem by exploiting the geometrical interpretation of the unmixing problem. This results in an algorithm which yields almost identical results as MESMA, but is computationally much more favorable." @default.
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- W2547938406 date "2016-07-01" @default.
- W2547938406 modified "2023-10-16" @default.
- W2547938406 title "Alternating angle minimization based unmixingwith endmember variability" @default.
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- W2547938406 doi "https://doi.org/10.1109/igarss.2016.7730819" @default.
- W2547938406 hasPublicationYear "2016" @default.
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