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dc.contributor.advisorCleary, David D.
dc.contributor.authorNikolaidis, Dimitrios.
dc.date.accessioned2013-04-30T22:05:17Z
dc.date.available2013-04-30T22:05:17Z
dc.date.issued1996-06
dc.identifier.urihttp://hdl.handle.net/10945/32109
dc.descriptionApplied Physicsen_US
dc.description.abstractThis study focuses on the development of computer algorithms that can be used for automatic mine detection using hyperspectral imagery. These algorithms perform a pixel-by-pixel comparison of the scene spectra with the spectrum of a mine. The goal is to assign to every pixel a scale factor which gives the relative probability of finding a mine. Algorithms were tested on simulated data taken from the NPS Middle Ultraviolet Spectrograph (MUSTANG). Three computer methods are tested and relative results were compared. This analysis suggests that the potential exists to use these methods in military applications. The ability to identify features in an image based solely on their spectral signature provides a new dimension to imagery interpretation.en_US
dc.description.urihttp://archive.org/details/detectionofmines1094532109
dc.format.extent53 p.en_US
dc.language.isoen_US
dc.publisherMonterey, California. Naval Postgraduate Schoolen_US
dc.titleDetection of mines using hyperspectral analysisen_US
dc.contributor.secondreaderSuntharalingam Gnanalingam.
dc.description.recognitionNAen_US
dc.description.serviceHellenic Navy author.en_US
etd.thesisdegree.nameM.S. in Applied Physicsen_US
etd.thesisdegree.levelMastersen_US
etd.thesisdegree.disciplineApplied Physicsen_US
etd.thesisdegree.grantorNaval Postgraduate Schoolen_US
dc.description.distributionstatementApproved for public release; distribution is unlimited.


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