Power spectra of the natural input to the visual system

DC ElementWertSprache
dc.contributor.authorPamplona, D.
dc.contributor.authorTriesch, J.
dc.contributor.authorRothkopf, C. A.
dc.date.accessioned2021-12-23T16:10:06Z-
dc.date.available2021-12-23T16:10:06Z-
dc.date.issued2013
dc.identifier.issn00426989
dc.identifier.urihttps://osnascholar.ub.uni-osnabrueck.de/handle/unios/9156-
dc.description.abstractThe efficient coding hypothesis posits that sensory systems are adapted to the regularities of their signal input so as to reduce redundancy in the resulting representations. It is therefore important to characterize the regularities of natural signals to gain insight into the processing of natural stimuli. While measurements of statistical regularity in vision have focused on photographic images of natural environments it has been much less investigated, how the specific imaging process embodied by the organism's eye induces statistical dependencies on the natural input to the visual system. This has allowed using the convenient assumption that natural image data are homogeneous across the visual field. Here we give up on this assumption and show how the imaging process in a human model eye influences the local statistics of the natural input to the visual system across the entire visual field. Artificial scenes with three-dimensional edge elements were generated and the influence of the imaging projection onto the back of a spherical model eye were quantified. These distributions show a strong radial influence of the imaging process on the resulting edge statistics with increasing eccentricity from the model fovea. This influence is further quantified through computation of the second order intensity statistics as a function of eccentricity from the center of projection using samples from the dead leaves image model. Using data from a naturalistic virtual environment, which allows generation of correctly projected images onto the model eye across the entire field of view, we quantified the second order dependencies as function of the position in the visual field using a new generalized parameterization of the power spectra. Finally, we compared this analysis with a commonly used natural image database, the van Hateren database, and show good agreement within the small field of view available in these photographic images. We conclude by providing a detailed quantitative analysis of the second order statistical dependencies of the natural input to the visual system across the visual field and demonstrating the importance of considering the influence of the sensory system on the statistical regularities of the input to the visual system. (C) 2013 Elsevier Ltd. All rights reserved.
dc.description.sponsorshipBMBF Project Bernstein Fokus: Neurotechnologie FrankfurtFederal Ministry of Education & Research (BMBF) [FKZ 01GQ0840]; This research was supported by the BMBF Project Bernstein Fokus: Neurotechnologie Frankfurt, FKZ 01GQ0840. The authors would like to thank Andrew Worzella for the help in generating the artificial images and the comments by one of the anonymous reviewers.
dc.language.isoen
dc.publisherPERGAMON-ELSEVIER SCIENCE LTD
dc.relation.ispartofVISION RESEARCH
dc.subjectCELLS
dc.subjectGAZE
dc.subjectIMAGE STATISTICS
dc.subjectINFORMATION
dc.subjectNatural image statistics
dc.subjectNatural vision
dc.subjectNeurosciences
dc.subjectNeurosciences & Neurology
dc.subjectOCCLUSIONS
dc.subjectOphthalmology
dc.subjectOrientation
dc.subjectPERCEPTION
dc.subjectPower spectrum
dc.subjectPsychology
dc.subjectREPRESENTATION
dc.subjectSCENES
dc.titlePower spectra of the natural input to the visual system
dc.typejournal article
dc.identifier.doi10.1016/j.visres.2013.01.011
dc.identifier.isiISI:000318202300008
dc.description.volume83
dc.description.startpage66
dc.description.endpage75
dc.contributor.orcid0000-0002-7843-8526
dc.publisher.placeTHE BOULEVARD, LANGFORD LANE, KIDLINGTON, OXFORD OX5 1GB, ENGLAND
dcterms.isPartOf.abbreviationVision Res.
dcterms.oaStatusBronze
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