Contrast discrimination in images of natural scenes

Triantaphillidou, S., Jarvis, J. and Gupta, G. 2022. Contrast discrimination in images of natural scenes. Journal of the Optical Society of America A. 39 (6), pp. B50-B64. https://doi.org/10.1364/JOSAA.447390

TitleContrast discrimination in images of natural scenes
TypeJournal article
AuthorsTriantaphillidou, S.
Jarvis, J.
Gupta, G.
Abstract

Contrast discrimination determines the threshold contrast required to distinguish between two suprathreshold visual stimuli. It is typically measured using sine-wave gratings. We first present a modification to Barten’s semi-mechanistic contrast discrimination model to account for spatial frequency effects and demonstrate how the model can successfully predict visual thresholds obtained from published classical contrast discrimination studies. Contrast discrimination functions are then measured from images of natural scenes, using a psychophysical paradigm based on that employed in our previous study of contrast detection sensitivity. The proposed discrimination model modification is shown to successfully predict discrimination thresholds for structurally very different types of natural image stimuli. A comparison of results shows that for normal contrast levels in natural scene viewing, contextual contrast detection and discrimination are approximately the same and almost independent of spatial frequency within the range of 1-20 c/deg. At higher frequencies both sensitivities decrease in magnitude due to optical limitations of the eye. The results are discussed in relation to current Image Quality models.

Keywordsnatural scenes
contrast discrimination
contrast sensitivity
image quality modeling
visual functions
JournalJournal of the Optical Society of America A
Journal citation39 (6), pp. B50-B64
ISSN1520-8532
Year2022
PublisherOptica
Accepted author manuscript
File Access Level
Open (open metadata and files)
Digital Object Identifier (DOI)https://doi.org/10.1364/JOSAA.447390
Web address (URL)https://opg.optica.org/josaa/abstract.cfm?URI=josaa-39-6-B50
Publication dates
Published27 Apr 2022
FunderDSTL (Defence Science & Technology Laboratory - MoD)

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