Optimal Class Separation in Hyperspectral Image Data: Iterated Canonical Discriminant Analysis

Allan Aasbjerg Nielsen; Andreas Müller

Optimal Class Separation in Hyperspectral Image Data: Iterated Canonical Discriminant Analysis

Allan Aasbjerg Nielsen
, Andreas Müller

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

Abstract

This paper describes canonical discriminant analysis and sketches an iterative version which is then applied to obtain optimal separation between a region, here examplified by either “water” or “wood/trees” and the rest of a HyMap image. We show that the iterative version greatly enhances the separation between the regions.

Original language	English
Publication date	2012
Number of pages	4
Publication status	Published - 2012
Event	Third Annual Hyperspectral Imaging Conference (HSI2012) - , Italy Duration: 15 May 2012 → 16 May 2012 Conference number: 3 http://istituto.ingv.it/l-ingv/convegni-e-seminari/archivio-congressi/convegni-2012/hsi2012-1/hsi2012/view

Conference

Conference	Third Annual Hyperspectral Imaging Conference (HSI2012)
Number	3
Country/Territory	Italy
Period	15/05/2012 → 16/05/2012
Internet address	http://istituto.ingv.it/l-ingv/convegni-e-seminari/archivio-congressi/convegni-2012/hsi2012-1/hsi2012/view

Keywords

Two-class discrimination
HyMap

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@conference{27988c8626cd4c1087a44a757000dc71,

title = "Optimal Class Separation in Hyperspectral Image Data: Iterated Canonical Discriminant Analysis",

abstract = "This paper describes canonical discriminant analysis and sketches an iterative version which is then applied to obtain optimal separation between a region, here examplified by either “water” or “wood/trees” and the rest of a HyMap image. We show that the iterative version greatly enhances the separation between the regions.",

keywords = "Two-class discrimination, HyMap",

author = "Nielsen, \{Allan Aasbjerg\} and Andreas M{\"u}ller",

year = "2012",

language = "English",

note = "Third Annual Hyperspectral Imaging Conference (HSI2012), HSI ; Conference date: 15-05-2012 Through 16-05-2012",

url = "http://istituto.ingv.it/l-ingv/convegni-e-seminari/archivio-congressi/convegni-2012/hsi2012-1/hsi2012/view",

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TY - CONF

T1 - Optimal Class Separation in Hyperspectral Image Data: Iterated Canonical Discriminant Analysis

AU - Nielsen, Allan Aasbjerg

AU - Müller, Andreas

N1 - Conference code: 3

PY - 2012

Y1 - 2012

N2 - This paper describes canonical discriminant analysis and sketches an iterative version which is then applied to obtain optimal separation between a region, here examplified by either “water” or “wood/trees” and the rest of a HyMap image. We show that the iterative version greatly enhances the separation between the regions.

AB - This paper describes canonical discriminant analysis and sketches an iterative version which is then applied to obtain optimal separation between a region, here examplified by either “water” or “wood/trees” and the rest of a HyMap image. We show that the iterative version greatly enhances the separation between the regions.

KW - Two-class discrimination

KW - HyMap

M3 - Paper

T2 - Third Annual Hyperspectral Imaging Conference (HSI2012)

Y2 - 15 May 2012 through 16 May 2012

ER -

Optimal Class Separation in Hyperspectral Image Data: Iterated Canonical Discriminant Analysis

Abstract

Conference

Keywords

OpenUrl availability

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Cite this