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Adaptation to blurred and sharpened video
Author(s) -
Andrew Haun,
Eli Peli
Publication year - 2013
Publication title -
journal of vision
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.126
H-Index - 113
ISSN - 1534-7362
DOI - 10.1167/13.8.12
Subject(s) - sharpening , adaptation (eye) , computer vision , artificial intelligence , computer science , motion blur , deblurring , image restoration , image (mathematics) , psychology , image processing , neuroscience
The visual system can distinguish different levels of blur and different levels of excess sharpness. Adaptation alters this capacity so that the adapted blur (or sharp) level looks more like a normal, properly focused image. Here, we describe the more general pattern of aftereffects of blur and sharp adaptation by measuring matching functions, using video clips from a DVD movie as stimuli. Results show that blur and sharp adaptation are selective: The sharpening aftereffects of blur adaptation are strongest for blurry videos while the blurring aftereffects of sharp adaptation are strongest for sharp videos. Despite the spatiotemporal variability of our adaptor and test stimuli, we found adaptation effects similar in magnitude to previous studies using invariant static images. A recent model of blur adaptation can be simplified to explain the form of our data, leading us to conclude that what we see as blur/sharp adaptation is a consequence of narrowband contrast adaptation.

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