August 2010
Volume 10, Issue 7
Free
Vision Sciences Society Annual Meeting Abstract  |   August 2010
The SHINE toolbox for controlling low-level image properties
Author Affiliations
  • Verena Willenbockel
    Département de Psychologie, Université de Montréal
  • Javid Sadr
    Department of Psychology, University of Massachusetts Boston
  • Daniel Fiset
    Département de Psychologie, Université de Montréal
  • Greg Horne
    Department of Psychology, University of Victoria
  • Frédéric Gosselin
    Département de Psychologie, Université de Montréal
  • James Tanaka
    Department of Psychology, University of Victoria
Journal of Vision August 2010, Vol.10, 653. doi:https://doi.org/10.1167/10.7.653
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      Verena Willenbockel, Javid Sadr, Daniel Fiset, Greg Horne, Frédéric Gosselin, James Tanaka; The SHINE toolbox for controlling low-level image properties. Journal of Vision 2010;10(7):653. https://doi.org/10.1167/10.7.653.

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      © ARVO (1962-2015); The Authors (2016-present)

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Abstract

Visual perception can be influenced by top-down processes related to the observer's goals and expectations, as well as by bottom-up processes related to low-level stimulus attributes, such as luminance, contrast, and spatial frequency. When using different physical stimuli across psychological conditions, one faces the problem of disentangling the contribution of low- and high-level factors. Here we make available the SHINE (Spectrum, Histogram, and Intensity Normalization and Equalization) toolbox written with Matlab, which we have found useful for controlling a number of image properties separately or simultaneously. SHINE features functions for scaling the rotational average of the Fourier amplitude spectra (i.e., the energy at each spatial frequency averaged across orientations), as well as for the precise matching of the spectra. It also includes functions for normalizing and scaling mean luminance and contrast, as well as a program for exact histogram specification. SHINE offers ways to apply the luminance adjustments to the whole image or to selective regions only (e.g., separately to the foreground and the background). The toolbox has been successfully employed for parametrically modifying a number of image properties or for equating them across the stimulus set in order to minimize potential low-level confounds in studies on higher-level processes (e.g., Fiset, Blais, Gosselin, Bub, & Tanaka, 2008; Williams, Willenbockel, & Gauthier, 2009). The toolbox can be downloaded here: www.mapageweb.umontreal.ca/gosselif/shine.

Willenbockel, V. Sadr, J. Fiset, D. Horne, G. Gosselin, F. Tanaka, J. (2010). The SHINE toolbox for controlling low-level image properties [Abstract]. Journal of Vision, 10(7):653, 653a, http://www.journalofvision.org/content/10/7/653, doi:10.1167/10.7.653. [CrossRef]
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