Paint manufacturers strive to introduce unique visual effects to coatings in order to visually communicate functional properties of products using value-added,customized design.However,these effects often feature complex,angularly dependent,spatially-varying behavior,thus representing a challenge in digital reproduction.In this paper we analyze several approaches to capturing spatially-varying appearances of effect coatings.We compare a baseline approach based on a bidirectional texture function (BTF) with four variants of half-difference parameterization.Through a psychophysical study,we determine minimal sampling along individual dimensions of this parameterization.We conclude that,compared to BTF,bivariate representations better preserve visual fidelity of effect coatings,better characterizing near-specular behavior and significantly the restricting number of images which must be captured.