Literature DB >> 33401176

Visual adaptation to natural scene statistics and visual preference.

Leena Yduyen Nguyen1, Branka Spehar2.   

Abstract

The amplitude of Fourier spectra for natural scenes falls with spatial frequency (f) and is described by the equation, 1/fα, where exponent α corresponds to the slope of the spectral drop-off. For natural scenes α takes on intermediate values ~1.25, reflecting their scale invariance. It is also well-established that, on average, images with natural scene statistics are preferred to those that deviate from these properties. Although this average pattern of preference for images with the intermediate values of α is robust, there are also marked individual differences in preference for different levels of α. This study investigated the effects of adaptation on average and individual visual preferences for synthetic filtered noise images varying in α. Participant preferences (N = 58) were measured via a 2AFC task prior to adaptation (baseline) and post-adaptation There were 3 adaptation conditions (α = 0.25, 1.25, 2.25) and 5 test levels of α (0.25, 0.75, 1.25, 1.75, 2.25). On average, the adaptation elevated preferences for test images with α matching the adaptor conditions, especially in adaptor conditions, α = 0.25 and 2.25. We also observed marked individual differences in preference for different levels of α. These different preference profiles remained stable throughout the experiment and affected the levels of adaptation observed in different adaptation conditions.
Copyright © 2020 Elsevier Ltd. All rights reserved.

Entities:  

Keywords:  Amplitude spectrum; Natural scene statistics; Visual adaptation; Visual preference

Mesh:

Year:  2021        PMID: 33401176     DOI: 10.1016/j.visres.2020.11.011

Source DB:  PubMed          Journal:  Vision Res        ISSN: 0042-6989            Impact factor:   1.886


  1 in total

1.  Regularity of colour statistics in explaining colour composition preferences in art paintings.

Authors:  Shigeki Nakauchi; Hideki Tamura
Journal:  Sci Rep       Date:  2022-08-26       Impact factor: 4.996

  1 in total

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