One-Class SVMs for Hyperspectral Anomaly Detection

Amit Banerjee, Philippe Burlina, Chris Diehl

Research output: Chapter in Book/Report/Conference proceeding › Chapter

Original languageEnglish (US)
Title of host publicationKernel Methods for Remote Sensing Data Analysis
PublisherJohn Wiley & Sons, Ltd
Pages169-192
Number of pages24
ISBN (Print)9780470722114
DOIs
StatePublished - Nov 4 2009

Keywords

  • Computational and detection performance of SVDD anomaly detectors
  • Goodness-of-fit test statistic for hyperspectral imagery based on Barringhaus, Henze, Epps and Pully (BHEP) test
  • Normalized metric appropriate for anomaly detection in spectral imagery
  • One-class SVMs for hyperspectral anomaly detection
  • Support Vector Data Description (SVDD)
  • Support vector framework for hyperspectral anomaly detection
  • SVDD algorithms for hyperspectral anomaly detection
  • SVDD derivation
  • SVDD function optimization

ASJC Scopus subject areas

  • Engineering(all)

Cite this

Banerjee, A., Burlina, P., & Diehl, C. (2009). One-Class SVMs for Hyperspectral Anomaly Detection. In Kernel Methods for Remote Sensing Data Analysis (pp. 169-192). John Wiley & Sons, Ltd. https://doi.org/10.1002/9780470748992.ch8

One-Class SVMs for Hyperspectral Anomaly Detection. / Banerjee, Amit; Burlina, Philippe; Diehl, Chris.

Kernel Methods for Remote Sensing Data Analysis. John Wiley & Sons, Ltd, 2009. p. 169-192.

Research output: Chapter in Book/Report/Conference proceeding › Chapter

Banerjee, A, Burlina, P & Diehl, C 2009, One-Class SVMs for Hyperspectral Anomaly Detection. in Kernel Methods for Remote Sensing Data Analysis. John Wiley & Sons, Ltd, pp. 169-192. https://doi.org/10.1002/9780470748992.ch8
Banerjee A, Burlina P, Diehl C. One-Class SVMs for Hyperspectral Anomaly Detection. In Kernel Methods for Remote Sensing Data Analysis. John Wiley & Sons, Ltd. 2009. p. 169-192 https://doi.org/10.1002/9780470748992.ch8
Banerjee, Amit ; Burlina, Philippe ; Diehl, Chris. / One-Class SVMs for Hyperspectral Anomaly Detection. Kernel Methods for Remote Sensing Data Analysis. John Wiley & Sons, Ltd, 2009. pp. 169-192
@inbook{7c5f6d953c12473783b37f147b75fb4a,
title = "One-Class SVMs for Hyperspectral Anomaly Detection",
keywords = "Computational and detection performance of SVDD anomaly detectors, Goodness-of-fit test statistic for hyperspectral imagery based on Barringhaus, Henze, Epps and Pully (BHEP) test, Normalized metric appropriate for anomaly detection in spectral imagery, One-class SVMs for hyperspectral anomaly detection, Support Vector Data Description (SVDD), Support vector framework for hyperspectral anomaly detection, SVDD algorithms for hyperspectral anomaly detection, SVDD derivation, SVDD function optimization",
author = "Amit Banerjee and Philippe Burlina and Chris Diehl",
year = "2009",
month = "11",
day = "4",
doi = "10.1002/9780470748992.ch8",
language = "English (US)",
isbn = "9780470722114",
pages = "169--192",
booktitle = "Kernel Methods for Remote Sensing Data Analysis",
publisher = "John Wiley & Sons, Ltd",

}

TY - CHAP

T1 - One-Class SVMs for Hyperspectral Anomaly Detection

AU - Banerjee, Amit

AU - Burlina, Philippe

AU - Diehl, Chris

PY - 2009/11/4

Y1 - 2009/11/4

KW - Computational and detection performance of SVDD anomaly detectors

KW - Goodness-of-fit test statistic for hyperspectral imagery based on Barringhaus, Henze, Epps and Pully (BHEP) test

KW - Normalized metric appropriate for anomaly detection in spectral imagery

KW - One-class SVMs for hyperspectral anomaly detection

KW - Support Vector Data Description (SVDD)

KW - Support vector framework for hyperspectral anomaly detection

KW - SVDD algorithms for hyperspectral anomaly detection

KW - SVDD derivation

KW - SVDD function optimization

UR - http://www.scopus.com/inward/record.url?scp=84856173037&partnerID=8YFLogxK

UR - http://www.scopus.com/inward/citedby.url?scp=84856173037&partnerID=8YFLogxK

U2 - 10.1002/9780470748992.ch8

DO - 10.1002/9780470748992.ch8

M3 - Chapter

SN - 9780470722114

SP - 169

EP - 192

BT - Kernel Methods for Remote Sensing Data Analysis

PB - John Wiley & Sons, Ltd

ER -

Access to Document