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Visual stream connectivity predicts assessments of image quality

Despite extensive study of early vision, new and unexpected mechanisms continue to be identified. We introduce a novel formal treatment of the psychophysics of image similarity, derived directly from straightforward connectivity patterns in early visual pathways. The resulting differential geometry...

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Detalles Bibliográficos
Autores principales: Bowen, Elijah F. W., Rodriguez, Antonio M., Sowinski, Damian R., Granger, Richard
Formato: Online Artículo Texto
Lenguaje:English
Publicado: The Association for Research in Vision and Ophthalmology 2022
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9580224/
https://www.ncbi.nlm.nih.gov/pubmed/36219145
http://dx.doi.org/10.1167/jov.22.11.4
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author Bowen, Elijah F. W.
Rodriguez, Antonio M.
Sowinski, Damian R.
Granger, Richard
author_facet Bowen, Elijah F. W.
Rodriguez, Antonio M.
Sowinski, Damian R.
Granger, Richard
author_sort Bowen, Elijah F. W.
collection PubMed
description Despite extensive study of early vision, new and unexpected mechanisms continue to be identified. We introduce a novel formal treatment of the psychophysics of image similarity, derived directly from straightforward connectivity patterns in early visual pathways. The resulting differential geometry formulation is shown to provide accurate and explanatory accounts of human perceptual similarity judgments. The direct formal predictions are then shown to be further improved via simple regression on human behavioral reports, which in turn are used to construct more elaborate hypothesized neural connectivity patterns. It is shown that the predictive approaches introduced here outperform a standard successful published measure of perceived image fidelity; moreover, the approach provides clear explanatory principles of these similarity findings.
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spelling pubmed-95802242022-10-20 Visual stream connectivity predicts assessments of image quality Bowen, Elijah F. W. Rodriguez, Antonio M. Sowinski, Damian R. Granger, Richard J Vis Article Despite extensive study of early vision, new and unexpected mechanisms continue to be identified. We introduce a novel formal treatment of the psychophysics of image similarity, derived directly from straightforward connectivity patterns in early visual pathways. The resulting differential geometry formulation is shown to provide accurate and explanatory accounts of human perceptual similarity judgments. The direct formal predictions are then shown to be further improved via simple regression on human behavioral reports, which in turn are used to construct more elaborate hypothesized neural connectivity patterns. It is shown that the predictive approaches introduced here outperform a standard successful published measure of perceived image fidelity; moreover, the approach provides clear explanatory principles of these similarity findings. The Association for Research in Vision and Ophthalmology 2022-10-11 /pmc/articles/PMC9580224/ /pubmed/36219145 http://dx.doi.org/10.1167/jov.22.11.4 Text en Copyright 2022 The Authors https://creativecommons.org/licenses/by/4.0/This work is licensed under a Creative Commons Attribution 4.0 International License.
spellingShingle Article
Bowen, Elijah F. W.
Rodriguez, Antonio M.
Sowinski, Damian R.
Granger, Richard
Visual stream connectivity predicts assessments of image quality
title Visual stream connectivity predicts assessments of image quality
title_full Visual stream connectivity predicts assessments of image quality
title_fullStr Visual stream connectivity predicts assessments of image quality
title_full_unstemmed Visual stream connectivity predicts assessments of image quality
title_short Visual stream connectivity predicts assessments of image quality
title_sort visual stream connectivity predicts assessments of image quality
topic Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9580224/
https://www.ncbi.nlm.nih.gov/pubmed/36219145
http://dx.doi.org/10.1167/jov.22.11.4
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