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dc.contributor.authorMcIlhagga, William H.*
dc.contributor.authorMay, K.A.*
dc.date.accessioned2014-04-28T10:55:36Z
dc.date.available2014-04-28T10:55:36Z
dc.date.issued2012
dc.identifier.citationMcIlhagga WH, May KA (2012) Optimal edge filters explain human blur detection. Journal of Vision. 12(10), 9, 1-13.
dc.identifier.urihttp://hdl.handle.net/10454/6091
dc.descriptionNo
dc.description.abstractEdges are important visual features, providing many cues to the three-dimensional structure of the world. One of these cues is edge blur. Sharp edges tend to be caused by object boundaries, while blurred edges indicate shadows, surface curvature, or defocus due to relative depth. Edge blur also drives accommodation and may be implicated in the correct development of the eye's optical power. Here we use classification image techniques to reveal the mechanisms underlying blur detection in human vision. Observers were shown a sharp and a blurred edge in white noise and had to identify the blurred edge. The resultant smoothed classification image derived from these experiments was similar to a derivative of a Gaussian filter. We also fitted a number of edge detection models (MIRAGE, N(1), and N(3)(+)) and the ideal observer to observer responses, but none performed as well as the classification image. However, observer responses were well fitted by a recently developed optimal edge detector model, coupled with a Bayesian prior on the expected blurs in the stimulus. This model outperformed the classification image when performance was measured by the Akaike Information Criterion. This result strongly suggests that humans use optimal edge detection filters to detect edges and encode their blur.
dc.language.isoen
dc.subjectBlur perception
dc.subjectContrast Sensitivity
dc.subjectPhysiology
dc.subjectClassification images
dc.subjectCues
dc.subjectEdge detection
dc.subjectHumans
dc.subjectModels
dc.subjectTheoretical
dc.subjectPhotic stimulation
dc.subjectPsychophysics
dc.subjectVisual perception
dc.subjectPhysiology
dc.subjectREF 2014
dc.titleOptimal edge filters explain human blur detection
dc.typeArticle
dc.type.versionNo full-text in the repository
dc.identifier.doihttps://doi.org/10.1167/12.11.7
dc.openaccess.statusclosedAccess


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