Detection of large targets in noisy hyper-spectral images

Eran Ohel; Stanley R. Rotman; Dan G. Blumberg

Detection of large targets in noisy hyper-spectral images

Eran Ohel, Stanley R. Rotman, Dan G. Blumberg

Research output: Contribution to conference › Paper › peer-review

Abstract

Basing ourselves on a novel segmentation algorithm for Hyper-Spectral Images (HSI), we have considered how to detect large targets (multi-pixel anomalous objects) in image cubes with a spectral component. In particular, we have developed several filters to compensate for speckle noise which may be present in the initial cube (and specifically in the target). We show that for speckle noise, a modification of our morphological technique allows us to detect targets without an enhanced false alarm result.

Original language	English
Pages	313-316
Number of pages	4
State	Published - 1 Dec 2004
Event	2004 23rd IEEE Convention of Electrical and Electronics Engineers in Israel, Proceedings - Tel-Aviv, Israel Duration: 6 Sep 2004 → 7 Sep 2004

Conference

Conference	2004 23rd IEEE Convention of Electrical and Electronics Engineers in Israel, Proceedings
Country/Territory	Israel
City	Tel-Aviv
Period	6/09/04 → 7/09/04

ASJC Scopus subject areas

Electrical and Electronic Engineering
Electronic, Optical and Magnetic Materials

Cite this

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title = "Detection of large targets in noisy hyper-spectral images",

abstract = "Basing ourselves on a novel segmentation algorithm for Hyper-Spectral Images (HSI), we have considered how to detect large targets (multi-pixel anomalous objects) in image cubes with a spectral component. In particular, we have developed several filters to compensate for speckle noise which may be present in the initial cube (and specifically in the target). We show that for speckle noise, a modification of our morphological technique allows us to detect targets without an enhanced false alarm result.",

author = "Eran Ohel and Rotman, {Stanley R.} and Blumberg, {Dan G.}",

year = "2004",

month = dec,

day = "1",

language = "English",

pages = "313--316",

note = "2004 23rd IEEE Convention of Electrical and Electronics Engineers in Israel, Proceedings ; Conference date: 06-09-2004 Through 07-09-2004",

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T1 - Detection of large targets in noisy hyper-spectral images

AU - Ohel, Eran

AU - Rotman, Stanley R.

AU - Blumberg, Dan G.

PY - 2004/12/1

Y1 - 2004/12/1

N2 - Basing ourselves on a novel segmentation algorithm for Hyper-Spectral Images (HSI), we have considered how to detect large targets (multi-pixel anomalous objects) in image cubes with a spectral component. In particular, we have developed several filters to compensate for speckle noise which may be present in the initial cube (and specifically in the target). We show that for speckle noise, a modification of our morphological technique allows us to detect targets without an enhanced false alarm result.

AB - Basing ourselves on a novel segmentation algorithm for Hyper-Spectral Images (HSI), we have considered how to detect large targets (multi-pixel anomalous objects) in image cubes with a spectral component. In particular, we have developed several filters to compensate for speckle noise which may be present in the initial cube (and specifically in the target). We show that for speckle noise, a modification of our morphological technique allows us to detect targets without an enhanced false alarm result.

UR - http://www.scopus.com/inward/record.url?scp=17444388930&partnerID=8YFLogxK

M3 - Paper

AN - SCOPUS:17444388930

SP - 313

EP - 316

T2 - 2004 23rd IEEE Convention of Electrical and Electronics Engineers in Israel, Proceedings

Y2 - 6 September 2004 through 7 September 2004

ER -

Detection of large targets in noisy hyper-spectral images

Abstract

Conference

ASJC Scopus subject areas

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