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Comments on «Automatic Target Detection for Sparse Hyperspectral Images» by Ahmad W. Bitar et al.

Abstract : In this technical report, we explain how our proposed sparse and low-rank matrix decomposition method for hyperspectral target detection, provided in our work «Automatic Target Detection for Sparse Hyperspectral Images [1]», can be extended to the lq norm (0 < q ≤ 1). Since the use of the l1 norm is still too far away from the ideal l0 norm, many non-convex regularizers, interpolated between the l0 norm and the l1 norm, have been proposed to better approximate the l0 norm.
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https://hal-centralesupelec.archives-ouvertes.fr/hal-02754410
Contributor : Ahmad W. Bitar Connect in order to contact the contributor
Submitted on : Wednesday, June 3, 2020 - 8:38:33 PM
Last modification on : Tuesday, December 14, 2021 - 3:01:54 AM
Long-term archiving on: : Friday, December 4, 2020 - 11:23:29 PM

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  • HAL Id : hal-02754410, version 1

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Ahmad W. Bitar, Ali Chehab, Jean-Philippe Ovarlez. Comments on «Automatic Target Detection for Sparse Hyperspectral Images» by Ahmad W. Bitar et al.. [Technical Report] American University of Beirut; CentraleSupélec, Université Paris-Saclay; ONERA -- The French Aerospace Lab. 2020. ⟨hal-02754410⟩

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