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Conference papers
SPECTRAL UNMIXING WITH SPARSITY AND STRUCTURING CONSTRAINTS
Abstract : This paper addresses the linear spectral unmixing problem, by incorporating different constraints that may be of interest in order to cope with spectral variability: sparsity (few nonzero abundances), group exclusivity (at most one nonzero abundance within subgroups of endmembers) and significance (non-zero abundances must exceed a threshold). We show how such problems can be solved exactly with mixed-integer programming techniques. Numerical simulations show that solutions can be computed for problems of limited, yet realistic , complexity, with improved estimation performance over existing methods, but with higher computing time. Index Terms-sparse spectral unmixing, L0-norm optimization , structured sparsity, mixed-integer programming.
Cited literature [15 references]
https://hal.archives-ouvertes.fr/hal-02051443
Contributor : Ramzi Ben Mhenni <>
Submitted on : Wednesday, February 27, 2019 - 5:34:25 PM
Last modification on : Monday, May 25, 2020 - 4:52:22 PM
Contributor : Ramzi Ben Mhenni <>
Submitted on : Wednesday, February 27, 2019 - 5:34:25 PM
Last modification on : Monday, May 25, 2020 - 4:52:22 PM
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BenMhenni_WHISPERS18.pdf
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