Performance Analysis of Robust Detectors for Hyperspectral Imaging

Joana Frontera-Pons 1 Jean-Philippe Ovarlez 1 Frédéric Pascal 1 Jocelyn Chanussot 2
1 SONDRA - Sondra, CentraleSupélec, Université Paris-Saclay
2 GIPSA-SIGMAPHY - SIGMAPHY
GIPSA-DIS - Département Images et Signal
Abstract : When accounting for heterogeneity and non-Gaussianity of real hyperspectral data, elliptical distributions provide reliable models for background characterization. Through these assumptions, this paper highlights the fact that robust estimation procedures are an interesting alternative to classical methods and can bring some great improvement to the detection process. The goal of this paper is then not only to recall well-known methodologies of target detection but also to propose ways to extend them for taking into account the heterogeneity and non-Gaussianity of the hyperspectral images.
Document type :
Conference papers
Complete list of metadatas
https://hal-supelec.archives-ouvertes.fr/hal-00934285
Contributor : Anne-Hélène Picot <>
Submitted on : Tuesday, January 21, 2014 - 5:24:19 PM
Last modification on : Friday, June 21, 2019 - 11:18:04 AM

Links full text

openaccess

Identifiers

Collections

ONERA | SUPELEC | SUP_E3S | SUP_SONDRA | GIPSA-SIGMAPHY | GIPSA-DIS | GIPSA | UGA | UGA-TEST-TER

Citation

Joana Frontera-Pons, Jean-Philippe Ovarlez, Frédéric Pascal, Jocelyn Chanussot. Performance Analysis of Robust Detectors for Hyperspectral Imaging. 2013 IEEE International Geoscience and Remote Sensing Symposium (IGARSS 2013), Jul 2013, Melbourne, Australia. pp.1-4, ⟨10.1109/IGARSS.2013.6721348⟩. ⟨hal-00934285⟩

Export

BibTeX TEI DC DCterms EndNote

Share

Metrics

Record views

439

Contact

CCSD