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Sparsity-based Cholesky Factorization and Its Application to Hyperspectral Anomaly Detection

Ahmad W. Bitar 1 Jean-Philippe Ovarlez 2, 1 Loong-Fah Cheong 3 
1 SONDRA - Sondra, CentraleSupélec, Université Paris-Saclay (COmUE)
2 ONERA - The French Aerospace Lab [Palaiseau]
3 NUS - National University of Singapore
Abstract : ****Some technical errors found in our published IEEE version are corrected here. So please read this paper on HAL instead of the IEEE version.***** We are humans and we all make mistakes. Sorry for any inconvenience.
Keywords : Hyperspectral anomaly detection covariance matrix Cholesky factor sparsity
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Submitted on : Tuesday, December 5, 2017 - 6:43:12 PM
Last modification on : Wednesday, November 3, 2021 - 6:55:35 AM

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ONERA | SUP_SONDRA | CENTRALESUPELEC | UNIV-PARIS-SACLAY | GS-ENGINEERING

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Ahmad W. Bitar, Jean-Philippe Ovarlez, Loong-Fah Cheong. Sparsity-based Cholesky Factorization and Its Application to Hyperspectral Anomaly Detection. 2017 IEEE 7th International Workshop on Computational Advances in Multi-Sensor Adaptive Processing (CAMSAP 2014), Dec 2017, Curaçao, Netherlands. ⟨10.1109/CAMSAP.2017.8313124⟩. ⟨hal-01656619⟩

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