Purchase this article with an account.
Barton L. Anderson, Jonathan Winawer; Layered image representations and the computation of surface lightness. Journal of Vision 2008;8(7):18. doi: 10.1167/8.7.18.
Download citation file:
© 2016 Association for Research in Vision and Ophthalmology.
A fundamental goal of research in the perception of surfaces is to understand the nature of the computations and representations underlying lightness perception. A significant challenge posed to the visual system is recovering surface lightness from the multiple physical causes that contribute to image luminance. One view asserts that the visual system decomposes the image into estimates of illumination, lightness, and transparency, generating layered image representations. More recent views have questioned the need to posit layered representations to explain lightness perception. Here, a number of demonstrations and experiments involving the perception of transparency are presented that reveal a critical role played by layered image representations in the computation of surface lightness. We provide new evidence demonstrating that the contrast relationships along contours can play a decisive role in determining whether images are decomposed into multiple layers, and that the constraints that regulate how this decomposition occurs can have a dramatic influence on perceived lightness.
This PDF is available to Subscribers Only