An update on the MATLAB hyperspectral image analysis toolbox

Samuel Rosario-Torres; Emmanuel Arzuaga-Cruz; Miguel Velez-Reyes; Luis O. Jiménez-Rodríguez

doi:10.1117/12.605674

An update on the MATLAB hyperspectral image analysis toolbox

Samuel Rosario-Torres
, Emmanuel Arzuaga-Cruz
, Miguel Velez-Reyes
, Luis O. Jiménez-Rodríguez

Univ. Puerto Rico at Mayagüez

Research output: Contribution to journal › Conference article › peer-review

2 Scopus citations

Abstract

The Hyperspectral Image Analysis Toolbox (HIAT) is a collection of algorithms that extend the capability of the MATLAB numerical computing environment for the processing of hyperspectral and multispectral imagery. The purpose of the HIAT Toolbox is to provide information extraction algorithms to users of hyperspectral and multispectral imagery in environmental and biomedical applications. HIAT has been developed as part of the NSF Center for Subsurface Sensing and Imaging (CenSSIS) Solutionware that seeks to develop a repository of reliable and reusable software tools that can be shared by researchers across research domains. HIAT provides easy access to supervised and unsupervised classification algorithms developed at LARSIP over the last 8 years.

Original language	English
Article number	76
Pages (from-to)	743-752
Number of pages	10
Journal	Proceedings of SPIE - The International Society for Optical Engineering
Volume	5806
Issue number	PART II
DOIs	https://doi.org/10.1117/12.605674
State	Published - 2005
Externally published	Yes
Event	Algorithms and Technologies for Multispectral, Hyperspectral, and Ultraspectral Imagery XI - Orlando, FL, United States Duration: 28 Mar 2005 → 01 Apr 2005

Keywords

Hyperspectral
Image Analysis
Supervised Classification
Unsupervised Classification

Access to Document

10.1117/12.605674

Cite this

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title = "An update on the MATLAB hyperspectral image analysis toolbox",

abstract = "The Hyperspectral Image Analysis Toolbox (HIAT) is a collection of algorithms that extend the capability of the MATLAB numerical computing environment for the processing of hyperspectral and multispectral imagery. The purpose of the HIAT Toolbox is to provide information extraction algorithms to users of hyperspectral and multispectral imagery in environmental and biomedical applications. HIAT has been developed as part of the NSF Center for Subsurface Sensing and Imaging (CenSSIS) Solutionware that seeks to develop a repository of reliable and reusable software tools that can be shared by researchers across research domains. HIAT provides easy access to supervised and unsupervised classification algorithms developed at LARSIP over the last 8 years.",

keywords = "Hyperspectral, Image Analysis, Supervised Classification, Unsupervised Classification",

author = "Samuel Rosario-Torres and Emmanuel Arzuaga-Cruz and Miguel Velez-Reyes and Jim{\'e}nez-Rodr{\'i}guez, \{Luis O.\}",

year = "2005",

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AU - Rosario-Torres, Samuel

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AU - Velez-Reyes, Miguel

AU - Jiménez-Rodríguez, Luis O.

PY - 2005

Y1 - 2005

N2 - The Hyperspectral Image Analysis Toolbox (HIAT) is a collection of algorithms that extend the capability of the MATLAB numerical computing environment for the processing of hyperspectral and multispectral imagery. The purpose of the HIAT Toolbox is to provide information extraction algorithms to users of hyperspectral and multispectral imagery in environmental and biomedical applications. HIAT has been developed as part of the NSF Center for Subsurface Sensing and Imaging (CenSSIS) Solutionware that seeks to develop a repository of reliable and reusable software tools that can be shared by researchers across research domains. HIAT provides easy access to supervised and unsupervised classification algorithms developed at LARSIP over the last 8 years.

AB - The Hyperspectral Image Analysis Toolbox (HIAT) is a collection of algorithms that extend the capability of the MATLAB numerical computing environment for the processing of hyperspectral and multispectral imagery. The purpose of the HIAT Toolbox is to provide information extraction algorithms to users of hyperspectral and multispectral imagery in environmental and biomedical applications. HIAT has been developed as part of the NSF Center for Subsurface Sensing and Imaging (CenSSIS) Solutionware that seeks to develop a repository of reliable and reusable software tools that can be shared by researchers across research domains. HIAT provides easy access to supervised and unsupervised classification algorithms developed at LARSIP over the last 8 years.

KW - Hyperspectral

KW - Image Analysis

KW - Supervised Classification

KW - Unsupervised Classification

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DO - 10.1117/12.605674

M3 - Conference article

AN - SCOPUS:27544447009

SN - 0277-786X

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EP - 752

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

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

IS - PART II

M1 - 76

T2 - Algorithms and Technologies for Multispectral, Hyperspectral, and Ultraspectral Imagery XI

Y2 - 28 March 2005 through 1 April 2005

ER -

An update on the MATLAB hyperspectral image analysis toolbox

Abstract

Keywords

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