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

Ahmad W. Bitar (1) , Ali Chehab (1) , Jean-Philippe Ovarlez (2, 3)

1 AUB - American University of Beirut [Beyrouth]
2 SONDRA - Sondra, CentraleSupélec, Université Paris-Saclay
3 DEMR, ONERA, Université Paris Saclay [Palaiseau]

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.

Domains: Signal and Image Processing; Mathematics [math]

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⟩