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Author Rosario, Dalton.

Title Statistical methods for analysis of hyperspectral anomaly detectors [electronic resource] / Dalton Rosario.

Imprint Adelphi, MD : Army Research Laboratory, [2007]


Location Call No. OPAC Message Status
 Axe Federal Documents Online  D 101.60/4:4266    ---  Available
Description viii, 86 pages : digital, PDF file.
text txt rdacontent
computer c rdamedia
online resource cr rdacarrier
Series ARL-TR ; 4266
ARL-TR (Aberdeen Proving Ground, Md.) ; 4266.
System Details Mode of access: Internet from the DTIC web site. Address as of 04/23/09: ; current access is available via PURL.
Note Title from title screen (viewed Apr. 23, 2009).
"September 2007."
Bibliography Includes bibliographical references (page 71).
Access Approved for public release.
Summary Most hyperspectral (HS) anomaly detectors in the literature have been evaluated using a few HS imagery sets to estimate the well-known ROC curve. Although this evaluation approach can be helpful in assessing detectors rates of correct detection and false alarm on a limited dataset, it does not shed lights on reasons for these detectors strengths and weaknesses using a significantly larger sample size. This paper discusses a more rigorous approach to testing and comparing HS anomaly detectors, and it is intended to serve as a guide for such a task. Using randomly generated samples, the approach introduces hypothesis tests for two different kinds of data: (i) idealized homogeneous samples and (ii) idealized heterogeneous samples, where model parameters can vary the difficulty level of these tests. In (i), a simulation experiment is devised to address a more generalized concern the expected degradation of correct detection as a function of increasing noise on a given alternative hypothesis. In (ii), fundamental features of a spectral sample (magnitude and shape) are modeled separately so that strengths and weaknesses of competing detectors can be independently assessed for each feature. Additionally, detectors ability to suppress transition of regions in the imagery is assessed in (ii).
Reproduction Electronic reproduction. Ft. Belvoir, Va. : Defense Technical Information Center, 2007.
Note s 2007 vau n s
Subject Optical detectors.
Atomic spectroscopy -- Statistical methods.
Probability density functions.
Statistics and probability.
Optical detection and detectors.
Atomic and molecular physics and spectroscopy.
False alarms.
Statistical analysis.
Statistical processes.
Hyperspectral imagery.
Added Author U.S. Army Research Laboratory.
Standard No. DTICE ADA480123
Gpo Item No. 0330-E (online)
Sudoc No. D 101.60/4:4266

Available items only