Material identification and classification in hyperspectral imagery using the normal compositional model

Using a linear subspace approach for invariant subpixel material identification in airborne hyperspectral imagery

Proceedings. 1999 IEEE Computer Society Conference on Computer Vision and Pattern Recognition (Cat. No PR00149) ◽

10.1109/cvpr.1999.786995 ◽

2003 ◽

Cited By ~ 1

Author(s):

B. Thai ◽

G. Healey

Keyword(s):

Linear Subspace ◽

Hyperspectral Imagery ◽

Material Identification

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Application of the normal compositional model to the analysis of hyperspectral imagery

IEEE Workshop on Advances in Techniques for Analysis of Remotely Sensed Data, 2003 ◽

10.1109/warsd.2003.1295171 ◽

2004 ◽

Cited By ~ 24

Author(s):

D. Stein

Keyword(s):

Hyperspectral Imagery ◽

Compositional Model

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Methods and challenges for target detection and material identification for longwave infrared hyperspectral imagery

10.1117/12.2225914 ◽

2016 ◽

Cited By ~ 1

Author(s):

Blake M. Rankin ◽

Joseph Meola ◽

David L. Perry ◽

Jason R. Kaufman

Keyword(s):

Target Detection ◽

Hyperspectral Imagery ◽

Material Identification

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Bayesian Estimation of Linear Mixtures Using the Normal Compositional Model. Application to Hyperspectral Imagery

IEEE Transactions on Image Processing ◽

10.1109/tip.2010.2042993 ◽

2010 ◽

Vol 19 (6) ◽

pp. 1403-1413 ◽

Cited By ~ 98

Author(s):

Olivier Eches ◽

Nicolas Dobigeon ◽

Corinne Mailhes ◽

Jean-Yves Tourneret

Keyword(s):

Bayesian Estimation ◽

Hyperspectral Imagery ◽

Model Application ◽

Compositional Model ◽

Linear Mixtures

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Exploiting an atmospheric model for automated invariant material identification in hyperspectral imagery

10.1117/12.312609 ◽

1998 ◽

Cited By ~ 12

Author(s):

David Slater ◽

Glenn Healey

Keyword(s):

Hyperspectral Imagery ◽

Atmospheric Model ◽

Material Identification

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Material identification using fuzzy-classification of high resolution hyperspectral imagery of an urban area

Optical Sensors and Sensing Congress (ES, FTS, HISE, Sensors) ◽

10.1364/hise.2019.htu3b.4 ◽

2019 ◽

Author(s):

Meghana Paranjape ◽

François Cavayas

Keyword(s):

High Resolution ◽

Urban Area ◽

Hyperspectral Imagery ◽

Fuzzy Classification ◽

Material Identification

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Models and methods for automated material identification in hyperspectral imagery acquired under unknown illumination and atmospheric conditions

IEEE Transactions on Geoscience and Remote Sensing ◽

10.1109/36.803418 ◽

1999 ◽

Vol 37 (6) ◽

pp. 2706-2717 ◽

Cited By ~ 130

Author(s):

G. Healey ◽

D. Slater

Keyword(s):

Hyperspectral Imagery ◽

Atmospheric Conditions ◽

Material Identification

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Ensemble learning and model averaging for material identification in hyperspectral imagery

10.1117/12.2263693 ◽

2017 ◽

Author(s):

William F. Basener

Keyword(s):

Ensemble Learning ◽

Hyperspectral Imagery ◽

Model Averaging ◽

Material Identification

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Biodiversity estimation technique using medium spatial resolution hyperspectral imagery

Kosmìčna nauka ì tehnologìâ ◽

10.15407/knit2007.04.025 ◽

2007 ◽

Vol 13 (4) ◽

pp. 25-39

Author(s):

S.A. Stankevich ◽

◽

A.O. Kozlova ◽

Keyword(s):

Spatial Resolution ◽

Hyperspectral Imagery ◽

Estimation Technique

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Metallic target material identification examined by the finite element method

Pollack Periodica ◽

10.1556/pollack.8.2013.3.6 ◽

2013 ◽

Vol 8 (3) ◽

pp. 59-68

Author(s):

Zoltán Pólik ◽

Zoltán Kántor

Keyword(s):

Finite Element Method ◽

Finite Element ◽

Target Material ◽

The Finite Element Method ◽

Material Identification ◽

Metallic Target ◽

Element Method

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