ArticleJournal of vision2015
Defocus blur discrimination in natural images with natural optics.
Article in Journal of vision, 2015. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 15 papers.
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Who cites it
15 citing papers in PubMed, 37 citations in OpenAlex.
- How distinct sources of nuisance variability in natural images and scenes limit human stereopsis.PLoS computational biology · 2025Article
- Impact of focus cue presentation on perceived realism of 3-D scene structure: Implications for scene perception and for display technology.Journal of vision · 2024Article
- Blur Representation in the Amblyopic Visual System Using Natural and Synthetic Images.Investigative ophthalmology & visual science · 2022Article
- Lags and leads of accommodation in humans: Fact or fiction?Journal of vision · 2021Article
- The blur horopter: Retinal conjugate surface in binocular viewing.Journal of vision · 2021Article
- Contact lenses, the reverse Pulfrich effect, and anti-Pulfrich monovision corrections.Scientific reports · 2020Article
- Natural scene statistics predict how humans pool information across space in surface tilt estimation.PLoS computational biology · 2020Article
- Predicting the Partition of Behavioral Variability in Speed Perception with Naturalistic Stimuli.The Journal of neuroscience : the official journal of the Society for Neuroscience · 2020Article
- Computational luminance constancy from naturalistic images.Journal of vision · 2018Article
- Depth variation and stereo processing tasks in natural scenes.Journal of vision · 2018Article
- Contributions of monocular and binocular cues to distance discrimination in natural scenes.Journal of vision · 2018Article
- Joint coding of shape and blur in area V4.Nature communications · 2018Article
- Vergence driven accommodation with simulated disparity in myopia and emmetropia.Experimental eye research · 2018Article
- Blur perception throughout the visual field in myopia and emmetropia.Journal of vision · 2017Article
- The natural statistics of blur.Journal of vision · 2016Article
Corrections and comments
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Authors and funding
3 authors at 2 institutions in 1 country.
Funding
Abstract
The lens system in the human eye is able to best focus light from only one distance at a time.Therefore, many objects in the natural environment are not imaged sharply on the retina. Furthermore, light from objects in the environment is subject to the particular aberrations of the observer's lens system (e.g., astigmatism and chromatic aberration). We refer to blur created by the observer's optics as "natural" or "defocus" blur as opposed to "on-screen" blur created by software on a display screen. Although blur discrimination has been studied extensively, human ability to discriminate defocus blur in images of natural scenes has not been systematically investigated. Here, we measured discrimination of defocus blur for a collection of natural image patches, sampled from well-focused photographs. We constructed a rig capable of presenting stimuli at three physical distances simultaneously. In Experiment 1, subjects viewed monocularly two simultaneously presented natural image patches through a 4-mm artificial pupil at ±1° eccentricity. The task was to identify the sharper patch. Discrimination thresholds varied substantially between stimuli but were correlated between subjects. The lowest thresholds were at or below the lowest thresholds ever reported. In a second experiment, we paralyzed accommodation and retested a subset of conditions from Experiment 1. A third experiment showed that removing contrast as a cue to defocus blur had only a modest effect on thresholds. Finally, we describe a simple masking model and evaluate how well it can explain our experimental results and the results from previous blur discrimination experiments.
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Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.