Geometrical interpretation of the adaptive coherence estimator for hyperspectral target detection

Shahar Bar; Ori Bass; Alon Volfman; Tomer Dallal; Stanley R. Rotman

doi:10.1117/12.2006472

Geometrical interpretation of the adaptive coherence estimator for hyperspectral target detection

Shahar Bar, Ori Bass, Alon Volfman, Tomer Dallal, Stanley R. Rotman

Ben-Gurion University of the Negev

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

3 Scopus citations

Abstract

A hyperspectral cube consists of a set of images taken at numerous wavelengths. Hyperspectral image data analysis uses each material's distinctive patterns of reflection, absorption and emission of electromagnetic energy at specific wavelengths for classification or detection tasks. Because of the size of the hyperspectral cube, data reduction is definitely advantageous; when doing this, one wishes to maintain high performances with the least number of bands. Obviously in such a case, the choice of the bands will be critical. In this paper, we will consider one particular algorithm, the adaptive coherence estimator (ACE) for the detection of point targets. We give a quantitative interpretation of the dependence of the algorithm on the number and identity of the bands that have been chosen. Results on simulated data will be presented.

Original language	English
Title of host publication	Algorithms and Technologies for Multispectral, Hyperspectral, and Ultraspectral Imagery XIX
DOIs	https://doi.org/10.1117/12.2006472
State	Published - 2013
Externally published	Yes
Event	Algorithms and Technologies for Multispectral, Hyperspectral, and Ultraspectral Imagery XIX - Baltimore, MD, United States Duration: 29 Apr 2013 → 2 May 2013

Publication series

Name	Proceedings of SPIE - The International Society for Optical Engineering
Volume	8743
ISSN (Print)	0277-786X
ISSN (Electronic)	1996-756X

Conference

Conference	Algorithms and Technologies for Multispectral, Hyperspectral, and Ultraspectral Imagery XIX
Country/Territory	United States
City	Baltimore, MD
Period	29/04/13 → 2/05/13

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10.1117/12.2006472

Cite this

Bar, S., Bass, O., Volfman, A., Dallal, T., & Rotman, S. R. (2013). Geometrical interpretation of the adaptive coherence estimator for hyperspectral target detection. In Algorithms and Technologies for Multispectral, Hyperspectral, and Ultraspectral Imagery XIX Article 87430K (Proceedings of SPIE - The International Society for Optical Engineering; Vol. 8743). https://doi.org/10.1117/12.2006472

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title = "Geometrical interpretation of the adaptive coherence estimator for hyperspectral target detection",

abstract = "A hyperspectral cube consists of a set of images taken at numerous wavelengths. Hyperspectral image data analysis uses each material's distinctive patterns of reflection, absorption and emission of electromagnetic energy at specific wavelengths for classification or detection tasks. Because of the size of the hyperspectral cube, data reduction is definitely advantageous; when doing this, one wishes to maintain high performances with the least number of bands. Obviously in such a case, the choice of the bands will be critical. In this paper, we will consider one particular algorithm, the adaptive coherence estimator (ACE) for the detection of point targets. We give a quantitative interpretation of the dependence of the algorithm on the number and identity of the bands that have been chosen. Results on simulated data will be presented.",

author = "Shahar Bar and Ori Bass and Alon Volfman and Tomer Dallal and Rotman, {Stanley R.}",

year = "2013",

doi = "10.1117/12.2006472",

language = "אנגלית",

isbn = "9780819495341",

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

booktitle = "Algorithms and Technologies for Multispectral, Hyperspectral, and Ultraspectral Imagery XIX",

note = "Algorithms and Technologies for Multispectral, Hyperspectral, and Ultraspectral Imagery XIX ; Conference date: 29-04-2013 Through 02-05-2013",

}

Bar, S, Bass, O, Volfman, A, Dallal, T & Rotman, SR 2013, Geometrical interpretation of the adaptive coherence estimator for hyperspectral target detection. in Algorithms and Technologies for Multispectral, Hyperspectral, and Ultraspectral Imagery XIX., 87430K, Proceedings of SPIE - The International Society for Optical Engineering, vol. 8743, Algorithms and Technologies for Multispectral, Hyperspectral, and Ultraspectral Imagery XIX, Baltimore, MD, United States, 29/04/13. https://doi.org/10.1117/12.2006472

Geometrical interpretation of the adaptive coherence estimator for hyperspectral target detection. / Bar, Shahar; Bass, Ori; Volfman, Alon et al.
Algorithms and Technologies for Multispectral, Hyperspectral, and Ultraspectral Imagery XIX. 2013. 87430K (Proceedings of SPIE - The International Society for Optical Engineering; Vol. 8743).

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

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T1 - Geometrical interpretation of the adaptive coherence estimator for hyperspectral target detection

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AB - A hyperspectral cube consists of a set of images taken at numerous wavelengths. Hyperspectral image data analysis uses each material's distinctive patterns of reflection, absorption and emission of electromagnetic energy at specific wavelengths for classification or detection tasks. Because of the size of the hyperspectral cube, data reduction is definitely advantageous; when doing this, one wishes to maintain high performances with the least number of bands. Obviously in such a case, the choice of the bands will be critical. In this paper, we will consider one particular algorithm, the adaptive coherence estimator (ACE) for the detection of point targets. We give a quantitative interpretation of the dependence of the algorithm on the number and identity of the bands that have been chosen. Results on simulated data will be presented.

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Geometrical interpretation of the adaptive coherence estimator for hyperspectral target detection

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