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SHINE_color: Controlling low-level properties of colorful images

Visual perception combines top-down processes arising from participants individual histories, such as expectations and goals, and bottom-up processes that arise from visual stimuli properties, such as luminance and contrast. The precise control of low-level visual stimuli properties is essential whe...

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Detalles Bibliográficos
Autor principal: Dal Ben, Rodrigo
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Elsevier 2023
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10522894/
https://www.ncbi.nlm.nih.gov/pubmed/37771500
http://dx.doi.org/10.1016/j.mex.2023.102377
Descripción
Sumario:Visual perception combines top-down processes arising from participants individual histories, such as expectations and goals, and bottom-up processes that arise from visual stimuli properties, such as luminance and contrast. The precise control of low-level visual stimuli properties is essential when investigating visual perception. Without it, for instance, investigations of bottom-up processes are virtually impossible and investigations of top-down processes risk major confounds when testing and formulating hypotheses. The SHINE (spectrum, histogram, and intensity normalization and equalization) toolbox for MATLAB [1] allows precise control of images’ Fourier amplitude spectra, the normalizing and scaling of luminance and contrast, and exact histogram specification optimized for perceptual visual quality. Following Willenbockel and Cols (2010) advices, here we present an adaptation of the SHINE toolbox, named SHINE_color, which extends SHINE functionalities by allowing the parametrical manipulation of low-level properties of both static and animated colorful images. • Parametric manipulation of low-level properties of colorful images; • Spectrum, histogram, and intensity normalization and equalization.