Predicting visible flicker in temporally changing images
Publication Date
2020-01-26Journal Title
Human Vision and Electronic Imaging 2020: Proceedings
Conference Name
Human Vision and Electronic Imaging 2020
ISSN
2470-1173
Publisher
Society for Imaging Sciences and Technology
Type
Conference Object
This Version
VoR
Metadata
Show full item recordCitation
Denes, G., & Mantiuk, R. (2020). Predicting visible flicker in temporally changing images. Human Vision and Electronic Imaging 2020: Proceedings https://doi.org/10.2352/ISSN.2470-1173.2020.11.HVEI-233
Abstract
Novel display algorithms such as low-persistence displays,
black frame insertion, and temporal resolution multiplexing in-
troduce temporal change into images at 40-180 Hz, on the bound-
ary of the temporal integration of the visual system. This can
lead to flicker, a highly-objectionable artifact known to induce
viewer discomfort. The critical flicker frequency (CFF) alone
does not model this phenomenon well, as flicker sensitivity varies
with contrast, and spatial frequency; a content-aware model is re-
quired. In this paper, we introduce a visual model for predicting
flicker visibility in temporally changing images. The model per-
forms a multi-scale analysis on the difference between consecu-
tive frames, normalizing values with the spatio-temporal contrast
sensitivity function as approximated by the pyramid of visibility.
The output of the model is a 2D detection probability map. We
ran a subjective flicker marking experiment to fit the model pa-
rameters, then analyze the difference between two display algo-
rithms, black frame insertion and temporal resolution multiplex-
ing, to demonstrate the application of our model.
Sponsorship
European Research Council (725253)
Engineering and Physical Sciences Research Council (1778303)
Embargo Lift Date
2100-01-01
Identifiers
External DOI: https://doi.org/10.2352/ISSN.2470-1173.2020.11.HVEI-233
This record's URL: https://www.repository.cam.ac.uk/handle/1810/301522
Rights
All rights reserved, Attribution 4.0 International
Licence URL: https://creativecommons.org/licenses/by/4.0/
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