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Author: Dalton Rosario

Affiliation: Army Research Laboratory, United States

ISBN: 972-8865-40-6

Keyword(s): Anomaly detection, Asymmetric hypothesis test, Hyperspectral imagery.

Related Ontology Subjects/Areas/Topics: Computer Vision, Visualization and Computer Graphics ; Early Vision and Image Representation ; Feature Extraction ; Features Extraction ; Image and Video Analysis ; Informatics in Control, Automation and Robotics ; Signal Processing, Sensors, Systems Modeling and Control ; Statistical Approach

Abstract: Local anomaly detectors have become quite popular for applications requiring hyperspectral (HS) target detection in natural clutter background assisted by an image analyst. Their popularity may be attributed to the simplicity of the algorithms designed to function as such. A disadvantage of using such detectors, however, is that they often produce an intolerable high number of detections per scene, which—according to image analysts—becomes a nuisance rather than an aiding tool. We present an effective local anomaly detector for HS data. The new detector exploits a notion of indirect comparison between two sets of samples and is free from distribution assumptions. The notion led us to derive a compact solution for a variance test, in which, under the null hypothesis, the detector’s performance converges to a known distribution. Experimental results using both simulated multivariate data and real HS data are presented to illustrate the effectiveness of this detector over five known alte rnative techniques. (More)

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Paper citation in several formats:
Rosario D. and (2006). A NOVEL ASYMMETRIC VARIANCE-BASED HYPOTHESIS TEST FOR A DIFFICULT SURVEILLANCE PROBLEM.In Proceedings of the First International Conference on Computer Vision Theory and Applications - Volume 1: VISAPP, ISBN 972-8865-40-6, pages 277-284. DOI: 10.5220/0001360802770284

@conference{visapp06,
author={Dalton Rosario},
title={A NOVEL ASYMMETRIC VARIANCE-BASED HYPOTHESIS TEST FOR A DIFFICULT SURVEILLANCE PROBLEM},
booktitle={Proceedings of the First International Conference on Computer Vision Theory and Applications - Volume 1: VISAPP,},
year={2006},
pages={277-284},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0001360802770284},
isbn={972-8865-40-6},
}

TY - CONF

JO - Proceedings of the First International Conference on Computer Vision Theory and Applications - Volume 1: VISAPP,
TI - A NOVEL ASYMMETRIC VARIANCE-BASED HYPOTHESIS TEST FOR A DIFFICULT SURVEILLANCE PROBLEM
SN - 972-8865-40-6
AU - Rosario, D.
PY - 2006
SP - 277
EP - 284
DO - 10.5220/0001360802770284

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