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dc.contributor.advisorVélez-Reyes, Miguel
dc.contributor.authorMasalmah, Yahya M.
dc.description.abstractIn hyperspectral imaging, hundreds of images are taken at narrow and contiguous spectral bands providing us with high spectral resolution spectral signatures that can be used to discriminate between objects. In many applications, the measured spectral signature is a mixture of the object of interest, and other objects within the field of view of the sensor. To determine which objects are in the field of view of the sensor, we need to decompose the measured spectral signature in its constituents and their contribution to the measured signal. This research dealt with the unsupervised determination of the constituents and their fractional abundance in each pixel in a hyperspectral image using a constrained positive matrix factorization (cPMF). Different algorithms are presented to compute the cPMF. Tests and validation with real and simulated data show the effectiveness of the method. Application of the approach to environmental remote sensing and microscopic imaging is shown.en_US
dc.description.sponsorshipThis work was partially supported by NSF Engineering Research Centers Program under grant EEC-9986821 and a Fellowship from the PR NASA Space Grant Program, Gordon Center for Subsurface Sensing and Imaging Systems (CenSSIS), and the Puerto Rico NASA Space Grant.en_US
dc.subjectHyperspectral imageryen_US
dc.subjectMatrix factorizationen_US
dc.titleUnsupervised unmixing of hyperspectral imagery using the constrained positive matrix factorization  en_US
dc.rights.licenseAll rights reserveden_US
dc.rights.holder(c) 2007 Yahya M. Masalmahen_US
dc.contributor.committeeHunt, Shawn
dc.contributor.committeeSantiago, Nayda
dc.contributor.committeeRivera, Wilson
dc.contributor.representativeGilbes, Fernando and Information Sciences and Engineeringen_US
dc.contributor.collegeCollege of Engineeringen_US
dc.contributor.departmentDepartment of Electrical and Computer Engineeringen_US

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    Items included under this collection are theses, dissertations, and project reports submitted as a requirement for completing a degree at UPR-Mayagüez.

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