Super-resolution by local function approximation

dc.contributor.committeeChairMonico, Christopher J.
dc.contributor.committeeMemberIyer, Ram V.
dc.contributor.committeeMemberMartin, Clyde
dc.creatorLawless, Steven
dc.date.accessioned2016-11-14T23:15:22Z
dc.date.available2012-06-01T16:42:45Z
dc.date.available2016-11-14T23:15:22Z
dc.date.issued2007-12
dc.degree.departmentMathematics
dc.description.abstractSuper-resolution estimates a higher resolution image given a set of lower resolution images with negligible scene differences between them. There are two key techniques developed for performing the super-resolution that is discussed in this paper. First, we develop an accurate alignment algorithm for the low-resolution images that takes into account any horizontal, vertical, and rotational shifts between the set of sample images. Second, a technique for approximating a higher resolution image by using sub-pixel level basis functions is developed.
dc.format.mimetypeapplication/pdf
dc.identifier.urihttp://hdl.handle.net/2346/13119
dc.language.isoeng
dc.rights.availabilityUnrestricted.
dc.subjectImage processing
dc.subjectSuper-resolution
dc.titleSuper-resolution by local function approximation
dc.typeThesis

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