Contributo in atti di convegno, 2022, ENG, 10.1109/IGARSS46834.2022.9883554

Bayesian Non-Parametric Detector Based on the Replacement Model

Matteoli, Stefania; Diani, Marco; Corsini, Giovanni

Università di Pisa; Consiglio Nazionale delle Ricerche; Italian Naval Academy

A Bayesian Likelihood Ratio Test (LRT) detector is analytically derived here for the replacement target model and using the non-parametric variable-bandwidth kernel density estimator to model the hyperspectral background. The detector is compared to the recent Generalized LRT detector, based on the same non-parametric model for the background. Experimental results obtained on two hyperspectral sub-pixel target detection scenarios reveal the great potential of the proposed detector and set the basis for future investigations.

IEEE International Geoscience and Remote Sensing Symposium, pp. 871–874, 2022

Keywords

Bayes, Hyperspectral, non-parametric, replacement model, Target Detection

CNR authors

Matteoli Stefania

CNR institutes

IEIIT – Istituto di elettronica e di ingegneria dell'informazione e delle telecomunicazioni

ID: 490818

Year: 2022

Type: Contributo in atti di convegno

Creation: 2023-12-28 17:38:17.000

Last update: 2024-01-09 09:56:20.000

External IDs

CNR OAI-PMH: oai:it.cnr:prodotti:490818

DOI: 10.1109/IGARSS46834.2022.9883554

Scopus: 2-s2.0-85140362814