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dc.contributor.advisorBovik, Alan C. (Alan Conrad), 1958-
dc.creatorKaser, Jennifer Yvonneen
dc.date.accessioned2013-12-09T20:27:23Zen
dc.date.accessioned2017-05-11T22:39:53Z
dc.date.available2017-05-11T22:39:53Z
dc.date.issued2013-08en
dc.date.submittedAugust 2013en
dc.identifier.urihttp://hdl.handle.net/2152/22601en
dc.descriptiontexten
dc.description.abstractWith the increasing number and affordability of image capture devices, there is an increasing demand to objectively analyze and compare the quality of images. Image quality can also be used as an indicator to determine if the source image is of high enough quality to perform analysis on. When applied to real world scenarios, use of a blind algorithm is essential since a flawless reference image typically is unavailable. Recent research has shown promising results in no reference image quality utilizing natural scene statistics in the visual image space. Research has also shown that although the statistical profiles vary slightly, there are statistical regularities in IR images as well which would indicate that natural scene statistical models may be able to be applied. In this project, I will analyze BRISQUE quality features of IR images and determine if the algorithm can successfully be applied to IR images. Additionally, in order to validate the usefulness of these techniques, the BRISQUE quality features are analyzed using a detection algorithm to determine if they can be used to predict conditions which may cause missed detections.en
dc.format.mimetypeapplication/pdfen
dc.language.isoen_USen
dc.subjectImage qualityen
dc.subjectBlind IQAen
dc.subjectNo reference IQAen
dc.subjectInfrared imageryen
dc.subjectThermal imageryen
dc.subjectNatural scene statisticsen
dc.titleUtilizing natural scene statistics and blind image quality analysis of infrared imageryen
dc.description.departmentElectrical and Computer Engineeringen
dc.date.updated2013-12-09T20:27:23Zen


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