The effect of scene articulation on transparent layer constancy.

Abstract

In this article, we examine the influence of scene articulation on transparent layer constancy. We argue that the term articulation may be understood as an aspect of the more general concept naturalness of a stimulus that relates to the degree of enrichment compared with a minimal stimulus and to the extent to which a stimulus contains regularities that are typically found in natural scenes. We conducted two matching experiments, in which we used strongly reduced scenes and operationalized articulation by the number of background reflectances (numerosity). The results of the first experiment show that higher numerosity actually leads to an increase in transparent layer constancy when reflectances are randomly drawn from a fixed population. However, this advantage disappears if the spatial mean and the variation of the subset colors are controlled as in our second experiment. Furthermore, our results suggest that the mechanism underlying transparent layer constancy leads to a rather stable compromise between two matching criteria, namely, proximal identity and constant filter properties according to our perceptual model. For filters with an additive component, which appear more or less hazy, we observed improved recovered filter properties and correspondingly higher degrees of transparent layer constancy, suggesting an additional mechanism in this type of filter.