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dc.contributor.advisorSai Ravela.en_US
dc.contributor.authorRunge, Joshua (Joshua Michael)en_US
dc.contributor.otherMassachusetts Institute of Technology. Dept. of Electrical Engineering and Computer Science.en_US
dc.date.accessioned2010-03-25T15:03:45Z
dc.date.available2010-03-25T15:03:45Z
dc.date.copyright2009en_US
dc.date.issued2009en_US
dc.identifier.urihttp://hdl.handle.net/1721.1/53120
dc.descriptionThesis (M. Eng.)--Massachusetts Institute of Technology, Dept. of Electrical Engineering and Computer Science, 2009.en_US
dc.descriptionIncludes bibliographical references (p. 45-46).en_US
dc.description.abstractThe goal of this thesis is to produce an image processing tool that could, with limited user interaction, significantly reduce spectral reflections. The resulting process can then be used by biological researchers in the process of cataloging and recognizing individual organisms via collected images. The process involves the generation of a mask, refinements to that mask such as background segmentation and morphological dilation, and finally the inpainting of the specular regions. This method improves on existing single pixel methods by incorporating both color and texture infilling of the specular reflections. It also works on images with no special setup or preparation.en_US
dc.description.statementofresponsibilityby Joshua Runge.en_US
dc.format.extent46 p.en_US
dc.language.isoengen_US
dc.publisherMassachusetts Institute of Technologyen_US
dc.rightsM.I.T. theses are protected by copyright. They may be viewed from this source for any purpose, but reproduction or distribution in any format is prohibited without written permission. See provided URL for inquiries about permission.en_US
dc.rights.urihttp://dspace.mit.edu/handle/1721.1/7582en_US
dc.subjectElectrical Engineering and Computer Science.en_US
dc.titleReducing spectral reflections through image inpaintingen_US
dc.typeThesisen_US
dc.description.degreeM.Eng.en_US
dc.contributor.departmentMassachusetts Institute of Technology. Department of Electrical Engineering and Computer Science
dc.identifier.oclc503142771en_US


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