An Automated Directed Spectral Search Methodology for Small Target Detection

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dc.contributor.advisorStefanidis, Tony
dc.contributor.authorGrossman, Stanley I.
dc.creatorGrossman, Stanley I.
dc.date.accessioned2014-09-18T01:56:08Z
dc.date.available2014-09-18T01:56:08Z
dc.date.issued2014-05
dc.description.abstractMuch of the current efforts in remote sensing tackle macro-level problems such as determining the extent of wheat in a field, the general health of vegetation or the extent of mineral deposits in an area. However, for many of the remaining remote sensing challenges being studied currently, such as border protection, drug smuggling, treaty verification, and the war on terror, most targets are very small in nature - a vehicle or even a person. While in typical macro-level problems the objective vegetation is in the scene, for small target detection problems it is not usually known if the desired small target even exists in the scene, never mind finding it in abundance. The ability to find specific small targets, such as vehicles, typifies this problem. Complicating the analyst's life, the growing number of available sensors is generating mountains of imagery outstripping the analysts' ability to visually peruse them.
dc.format.extent191 pages
dc.identifier.urihttps://hdl.handle.net/1920/8885
dc.language.isoen
dc.rightsCopyright 2014 Stanley I. Grossman
dc.subjectRemote sensing
dc.subjectAnalytic sweet spot
dc.subjectAutomated target detection
dc.subjectDirected search
dc.subjectNearest neighbor inflation
dc.subjectSpectral searach
dc.titleAn Automated Directed Spectral Search Methodology for Small Target Detection
dc.typeDissertation
thesis.degree.disciplineEarth Systems and Geoinformation Sciences
thesis.degree.grantorGeorge Mason University
thesis.degree.levelDoctoral

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