A Semiparametric Model for Hyperspectral Anomaly Detection
Author
Source
Journal of Electrical and Computer Engineering
Issue
Vol. 2012, Issue 2012 (31 Dec. 2012), pp.1-30, 30 p.
Publisher
Hindawi Publishing Corporation
Publication Date
2012-11-19
Country of Publication
Egypt
No. of Pages
30
Main Subjects
Engineering Sciences and Information Technology
Information Technology and Computer Science
Abstract EN
Using hyperspectral (HS) technology, this paper introduces an autonomous scene anomaly detection approach based on the asymptotic behavior of a semiparametric model under a multisample testing and minimum-order statistic scheme.
Scene anomaly detection has a wide range of use in remote sensing applications, requiring no specific material signatures.
Uniqueness of the approach includes the following: (i) only a small fraction of the HS cube is required to characterize the unknown clutter background, while existing global anomaly detectors require the entire cube; (ii) the utility of a semiparematric model, where underlying distributions of spectra are not assumed to be known but related through an exponential function; (iii) derivation of the asymptotic cumulative probability of the approach making mistakes, allowing the user some control of probabilistic errors.
Results using real HS data are promising for autonomous manmade object detection in difficult natural clutter backgrounds from two viewing perspectives: nadir and forward looking.
American Psychological Association (APA)
Rosario, Dalton. 2012. A Semiparametric Model for Hyperspectral Anomaly Detection. Journal of Electrical and Computer Engineering،Vol. 2012, no. 2012, pp.1-30.
https://search.emarefa.net/detail/BIM-471230
Modern Language Association (MLA)
Rosario, Dalton. A Semiparametric Model for Hyperspectral Anomaly Detection. Journal of Electrical and Computer Engineering No. 2012 (2012), pp.1-30.
https://search.emarefa.net/detail/BIM-471230
American Medical Association (AMA)
Rosario, Dalton. A Semiparametric Model for Hyperspectral Anomaly Detection. Journal of Electrical and Computer Engineering. 2012. Vol. 2012, no. 2012, pp.1-30.
https://search.emarefa.net/detail/BIM-471230
Data Type
Journal Articles
Language
English
Notes
Includes bibliographical references
Record ID
BIM-471230