Skip to Main content Skip to Navigation
Conference papers

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 : sparsity Cholesky factor covariance matrix Hyperspectral anomaly detection
Document type :
Conference papers
Complete list of metadata

Cited literature [34 references]  Display  Hide  Download
https://hal-centralesupelec.archives-ouvertes.fr/hal-01656619
Contributor : Ahmad W. Bitar Connect in order to contact the contributor
Submitted on : Tuesday, December 5, 2017 - 6:43:12 PM
Last modification on : Wednesday, November 3, 2021 - 6:55:35 AM

File

Vignette du document
bare_conf.pdf
Files produced by the author(s)

Identifiers

Collections

CENTRALESUPELEC | ONERA | SUP_SONDRA | GS-ENGINEERING

Citation

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⟩

Export

BibTeX TEI DC DCterms EndNote

Share

Metrics

Les métriques sont temporairement indisponibles