Abstract
The spectral reflectance function of a surface specifies the fraction of the illumination reflected by it at each wavelength. Jointly with the illumination spectral density, this function determines the apparent colour of the surface. Models for the distribution of spectral reflectance functions in the natural environment are considered. The realism of the models is assessed in terms of the individual reflectance functions they generate, and in terms of the overall distribution of colours which they give rise to. Both realism assessments are made in comparison to empirical datasets. Previously described models (PCA- and fourier-based) of reflectance function statistics are evaluated, as are improved versions; and also a novel model, which synthesizes reflectance functions as a sum of sigmoid functions. Key model features for realism are identified. The new sigmoid-sum model is shown to be the most realistic, generating reflectance functions that are hard to distinguish from real ones, and accounting for the majority of colours found in natural images with the exception of an abundance of vegetation green and sky blue.
Highlights
A viewer sees an illuminated surface—the light arriving at their eye being determined by the intensity of the illuminant and the reflectance of the surface, both as a function of wavelength— and declares it ‘green’
Most prized are mechanistic models linking adjacent levels, and much has been achieved in colour science: electromagnetic models describe the interaction of the illumination with the scene [7]; optical ones, the formation of the retinal image [8]; electro-physiological, the retinal cone transduction of light into a nerve impulse [9,10,11]); and neuronal, the re-coding of sensory responses into opponent channel representations [12]
Correct frequency content alone does not lead to the localized transitions that are visible in some empirical reflectance functions
Summary
A viewer sees an illuminated surface—the light arriving at their eye being determined by the intensity of the illuminant and the reflectance of the surface, both as a function of wavelength— and declares it ‘green’. The causal sequence underlying this threads through Popper’s three levels of reality [1]: world I, matter and sensation; world II, perception and cognition; world III, language and culture. Most prized are mechanistic models linking adjacent levels, and much has been achieved in colour science: electromagnetic models describe the interaction of the illumination with the scene [7]; optical ones, the formation of the retinal image [8]; electro-physiological, the retinal cone transduction of light into a nerve impulse [9,10,11]); and neuronal, the re-coding of sensory responses into opponent channel representations [12]. Mechanistic models are not feasible, but accurate predictive models may still be; for example, colour naming atlases [13, 14] that link sensory responses to language.
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