A Robust Variable Order Facet Model for Image Data

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dc.contributor.authorMainguy, Y.en
dc.contributor.authorBirch, Jeffrey B.en
dc.contributor.authorWatson, Layne T.en
dc.contributor.departmentComputer Scienceen
dc.date.accessioned2013-06-19T14:36:21Zen
dc.date.available2013-06-19T14:36:21Zen
dc.date.issued1991en
dc.description.abstractIt is a common practice in computer vision and image processing to convolve rectangular constant coefficient windows with digital images to perform local smoothing and derivative estimation for edge detection and other purposes. If all data points in each image window belong to the same statistical population, this practice is reasonable and fast. But, as is well known, constant coefficient window operators produce incorrect results if more than one statistical population is present within a window, e.g., if a gray level or gradient discontinuity is present. This paper shows one way to apply the theory of robust statistics to the data smoothing and derivative estimation problem. A robust window operator is demonstrated that preserves gray level and gradient discontinuities in digital images as it smooths and estimates derivatives.en
dc.format.mimetypeapplication/pdfen
dc.identifierhttp://eprints.cs.vt.edu/archive/00000278/en
dc.identifier.sourceurlhttp://eprints.cs.vt.edu/archive/00000278/01/TR-91-33.pdfen
dc.identifier.trnumberTR-91-33en
dc.identifier.urihttp://hdl.handle.net/10919/19690en
dc.language.isoenen
dc.publisherDepartment of Computer Science, Virginia Polytechnic Institute & State Universityen
dc.relation.ispartofHistorical Collection(Till Dec 2001)en
dc.rightsIn Copyrighten
dc.rights.urihttp://rightsstatements.org/vocab/InC/1.0/en
dc.titleA Robust Variable Order Facet Model for Image Dataen
dc.typeTechnical reporten
dc.type.dcmitypeTexten

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