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Proceedings Paper

New developments and application of the UPRM MATLAB hyperspectral image analysis toolbox
Author(s): Samuel Rosario-Torres; Miguel Vélez-Reyes; Shawn D. Hunt; Luis O. Jiménez
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Paper 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 the Toolbox is to provide a suite of information extraction algorithms to users of hyperspectral and multispectral imagery. 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 feature extraction/selection, supervised and unsupervised classification algorithms, unmixing and visualization developed at Laboratory of Remote Sensing and Image Processing (LARSIP). This paper presents an overview of the tools, application available in HIAT using as example an AVIRIS image. In addition, we present the new HIAT developments, unmixing, new oversampling algorithm, true color visualization, crop tool and GUI enhancement.

Paper Details

Date Published: 7 May 2007
PDF: 12 pages
Proc. SPIE 6565, Algorithms and Technologies for Multispectral, Hyperspectral, and Ultraspectral Imagery XIII, 65650E (7 May 2007); doi: 10.1117/12.721051
Show Author Affiliations
Samuel Rosario-Torres, Univ. of Puerto Rico, Mayagüez (United States)
Miguel Vélez-Reyes, Univ. of Puerto Rico, Mayagüez (United States)
Shawn D. Hunt, Univ. of Puerto Rico, Mayagüez (United States)
Luis O. Jiménez, Univ. of Puerto Rico, Mayagüez (United States)


Published in SPIE Proceedings Vol. 6565:
Algorithms and Technologies for Multispectral, Hyperspectral, and Ultraspectral Imagery XIII
Sylvia S. Shen; Paul E. Lewis, Editor(s)

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