Improved covariance equalization for change detection in hyperspectral images

Nofar Piri; Eden Nisanov; Erez Yardeni; Stanley R. Rotman

doi:10.1117/12.2584038

Improved covariance equalization for change detection in hyperspectral images

Nofar Piri, Eden Nisanov, Erez Yardeni, Stanley R. Rotman

Department of Electrical & Computer Engineering

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

Abstract

This paper will focus on analyzing the Covariance Equalization (CE) change detection algorithm for hyperspectral data. We analyze its weaknesses and suggest a method to improve the algorithm using normalization.

Original language	English
Title of host publication	Algorithms, Technologies, and Applications for Multispectral and Hyperspectral Imaging XXVII
Editors	Miguel Velez-Reyes, David W. Messinger
Publisher	SPIE
ISBN (Electronic)	9781510642911
DOIs	https://doi.org/10.1117/12.2584038
State	Published - 1 Jan 2021
Event	Algorithms, Technologies, and Applications for Multispectral and Hyperspectral Imaging XXVII 2021 - Virtual, Online, United States Duration: 12 Apr 2021 → 16 Apr 2021

Publication series

Name	Proceedings of SPIE - The International Society for Optical Engineering
Volume	11727
ISSN (Print)	0277-786X
ISSN (Electronic)	1996-756X

Conference

Conference	Algorithms, Technologies, and Applications for Multispectral and Hyperspectral Imaging XXVII 2021
Country/Territory	United States
City	Virtual, Online
Period	12/04/21 → 16/04/21

Keywords

Covariance Equalization
Hyperspectral
Hyperspectral image
Target detection

ASJC Scopus subject areas

Electronic, Optical and Magnetic Materials
Condensed Matter Physics
Computer Science Applications
Applied Mathematics
Electrical and Electronic Engineering

Access to Document

10.1117/12.2584038

Cite this

Piri, N., Nisanov, E., Yardeni, E., & Rotman, S. R. (2021). Improved covariance equalization for change detection in hyperspectral images. In M. Velez-Reyes, & D. W. Messinger (Eds.), Algorithms, Technologies, and Applications for Multispectral and Hyperspectral Imaging XXVII Article 1172708 (Proceedings of SPIE - The International Society for Optical Engineering; Vol. 11727). SPIE. https://doi.org/10.1117/12.2584038

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title = "Improved covariance equalization for change detection in hyperspectral images",

abstract = "This paper will focus on analyzing the Covariance Equalization (CE) change detection algorithm for hyperspectral data. We analyze its weaknesses and suggest a method to improve the algorithm using normalization.",

keywords = "Covariance Equalization, Hyperspectral, Hyperspectral image, Target detection",

author = "Nofar Piri and Eden Nisanov and Erez Yardeni and Rotman, {Stanley R.}",

note = "Publisher Copyright: {\textcopyright} 2021 SPIE.; Algorithms, Technologies, and Applications for Multispectral and Hyperspectral Imaging XXVII 2021 ; Conference date: 12-04-2021 Through 16-04-2021",

year = "2021",

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doi = "10.1117/12.2584038",

language = "English",

series = "Proceedings of SPIE - The International Society for Optical Engineering",

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Piri, N, Nisanov, E, Yardeni, E & Rotman, SR 2021, Improved covariance equalization for change detection in hyperspectral images. in M Velez-Reyes & DW Messinger (eds), Algorithms, Technologies, and Applications for Multispectral and Hyperspectral Imaging XXVII., 1172708, Proceedings of SPIE - The International Society for Optical Engineering, vol. 11727, SPIE, Algorithms, Technologies, and Applications for Multispectral and Hyperspectral Imaging XXVII 2021, Virtual, Online, United States, 12/04/21. https://doi.org/10.1117/12.2584038

Improved covariance equalization for change detection in hyperspectral images. / Piri, Nofar; Nisanov, Eden; Yardeni, Erez et al.
Algorithms, Technologies, and Applications for Multispectral and Hyperspectral Imaging XXVII. ed. / Miguel Velez-Reyes; David W. Messinger. SPIE, 2021. 1172708 (Proceedings of SPIE - The International Society for Optical Engineering; Vol. 11727).

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

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T1 - Improved covariance equalization for change detection in hyperspectral images

AU - Piri, Nofar

AU - Nisanov, Eden

AU - Yardeni, Erez

AU - Rotman, Stanley R.

PY - 2021/1/1

Y1 - 2021/1/1

N2 - This paper will focus on analyzing the Covariance Equalization (CE) change detection algorithm for hyperspectral data. We analyze its weaknesses and suggest a method to improve the algorithm using normalization.

AB - This paper will focus on analyzing the Covariance Equalization (CE) change detection algorithm for hyperspectral data. We analyze its weaknesses and suggest a method to improve the algorithm using normalization.

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KW - Hyperspectral

KW - Hyperspectral image

KW - Target detection

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M3 - Conference contribution

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T3 - Proceedings of SPIE - The International Society for Optical Engineering

BT - Algorithms, Technologies, and Applications for Multispectral and Hyperspectral Imaging XXVII

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T2 - Algorithms, Technologies, and Applications for Multispectral and Hyperspectral Imaging XXVII 2021

Y2 - 12 April 2021 through 16 April 2021

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Piri N, Nisanov E, Yardeni E, Rotman SR. Improved covariance equalization for change detection in hyperspectral images. In Velez-Reyes M, Messinger DW, editors, Algorithms, Technologies, and Applications for Multispectral and Hyperspectral Imaging XXVII. SPIE. 2021. 1172708. (Proceedings of SPIE - The International Society for Optical Engineering). doi: 10.1117/12.2584038

Improved covariance equalization for change detection in hyperspectral images

Abstract

Publication series

Conference

Keywords

ASJC Scopus subject areas

Access to Document

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