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Models for discriminating image blur from loss of contrast

Solomon, J. A. ORCID: 0000-0001-9976-4788 & Morgan, M. J. (2020). Models for discriminating image blur from loss of contrast. Journal of Vision, 20(6), article number 19. doi: 10.1167/jov.20.6.19


Observers can discriminate between blurry and low-contrast images (Morgan, 2017). Wang and Simoncelli (2004) demonstrated that a code for blur is inherent to the phase relationships between localized pattern detectors of different scale. To test whether human observers actually use local phase coherence when discriminating between image blur and loss of contrast, we compared phase-scrambled chessboards with unscrambled chessboards. Although both stimuli had identical amplitude spectra, local phase coherence was disrupted by phase-scrambling. Human observers were required to concurrently detect and identify (as contrast or blur) image manipulations in the 2x2 forced-choice paradigm (Nachmias & Weber, 1975; Watson & Robson, 1981) traditionally considered to be a litmus test for "labelled lines" (i.e. detection mechanisms that can be distinguished on the basis of their preferred stimuli). Phase scrambling reduced some observers’ ability to discriminate between blur and a reduction in contrast. However, none of our observers produced data consistent with Watson & Robson’s most stringent test for labelled lines, regardless whether phases were scrambled or not. Models of performance fit significantly better when either a) the blur detector also responded to contrast modulations, b) the contrast detector also responded to blur modulations, or c) noise in the two detectors was anticorrelated

Publication Type: Article
Publisher Keywords: Detection, Modeling, Psychophysics
Subjects: R Medicine > RE Ophthalmology
Departments: School of Health & Psychological Sciences > Optometry & Visual Sciences
SWORD Depositor:
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Available under License Creative Commons Attribution Non-commercial No Derivatives.

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