Bayesian Target Detection Algorithms for Solid Subpixel Targets in Hyperspectral Images
Author:
Affiliation:
1. Institute of Electronics, Information Engineering and Telecommunications (IEIIT), Consiglio Nazionale delle Ricerche (CNR), Pisa, Italy
2. Space Remote Sensing and Data Science Group, Los Alamos National Laboratory, Los Alamos, NM, USA
Funder
Laboratory Directed Research and Development (LDRD) Program at the Los Alamos National Laboratory, Los Alamos, NM, USA
Publisher
Institute of Electrical and Electronics Engineers (IEEE)
Subject
General Earth and Planetary Sciences,Electrical and Electronic Engineering
Link
http://xplorestaging.ieee.org/ielx7/36/10006360/10172300.pdf?arnumber=10172300
Reference35 articles.
1. An Overview of Background Modeling for Detection of Targets and Anomalies in Hyperspectral Remotely Sensed Imagery
2. An analysis task comparison of uncorrected vs. geo-registered airborne hyperspectral imagery;sun;Proc SPIE,2015
3. Veritas: an admissible detector for targets of unknown strength
4. SHARE 2012: subpixel detection and unmixing experiments
5. EC-GLRT: Detecting Weak Plumes in Non-Gaussian Hyperspectral Clutter Using an Elliptically-Contoured Generalized Likelihood Ratio Test
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