The relationship between language and the environment: information theory shows why we have only three lightness terms.

The surface reflectance of objects is highly variable, ranging between 4% for, say, charcoal and 90% for fresh snow. When stimuli are presented simultaneously, people can discriminate hundreds of levels of visual intensity. Despite this, human languages possess a maximum of just three basic terms for describing lightness. In English, these are white (or light), black (or dark), and gray. Why should this be? Using information theory, combined with estimates of the distribution of reflectances in the natural world and the reliability of lightness recall over time, we show that three lightness terms is the optimal number for describing surface reflectance properties in a modern urban or indoor environment. We also show that only two lightness terms would be required in a forest or rural environment.

The distribution of reflectances within the visual environment.

The statistics of natural images have often been used to account for various properties of animal visual systems. However, for most visual tasks, the images themselves are not important; it is the physical properties of the surfaces which generated them that guide behaviour. Here, we present statistical characterisations of the surface reflectances encountered within four different visual environments (woodland, beach, urban and interior), sampled using a systematic, survey-based method. Of the distributions fitted to the data, the beta distribution provides the best description per number of free parameters. Such distributions may be used as priors in Bayesian models of lightness constancy, or to generate ecologically valid reflectance distributions for simulated environments. The implications of this for models of reflectance extraction within visual systems are discussed.