Displaying Confidence Images

dc.contributor.authorNagy, James G.en_US
dc.contributor.authorO'Leary, Dianne P.en_US
dc.date.accessioned2004-05-31T23:05:48Z
dc.date.available2004-05-31T23:05:48Z
dc.date.created2000-07en_US
dc.date.issued2000-07-20en_US
dc.description.abstractAlgorithms for computing images result in an estimate of an image. The image may result from deblurring a measured image, from deconvolving a set of measurements, or from computing an image by modeling physical processes such as the weather. These computations provide an estimated value for each pixel in the image. What is lacking, however, is an estimate of the statistical confidence that we can have in those pixel values or in the features they form. In this work we discuss novel ways to display confidence information, using an algorithm called {\sf Twinkle}, in order to give the viewer valuable visual insight into uncertainties. The technique is useful whether the confidence information is in the form of a confidence interval or a distribution of possible values. We demonstrate how to display confidence information in a variety of applications: weather forecasts, intensity of a star, and rating a potential tumor in a diagnostic image. (Also cross-referenced as UMIACS-TR-2000-51)en_US
dc.format.extent1624246 bytes
dc.format.mimetypeapplication/postscript
dc.identifier.urihttp://hdl.handle.net/1903/1089
dc.language.isoen_US
dc.relation.isAvailableAtDigital Repository at the University of Marylanden_US
dc.relation.isAvailableAtUniversity of Maryland (College Park, Md.)en_US
dc.relation.isAvailableAtTech Reports in Computer Science and Engineeringen_US
dc.relation.isAvailableAtUMIACS Technical Reportsen_US
dc.relation.ispartofseriesUM Computer Science Department; CS-TR-4161en_US
dc.relation.ispartofseriesUMIACS; UMIACS-TR-2000-51en_US
dc.titleDisplaying Confidence Imagesen_US
dc.typeTechnical Reporten_US

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