Is lightness induction a pictorial illusion?

Bioplausible multiscale filtering in retino-cortical processing as a mechanism in perceptual grouping

Why does our visual system fail to reconstruct reality, when we look at certain patterns? Where do Geometrical illusions start to emerge in the visual pathway? How far should we take computational models of vision with the same visual ability to detect illusions as we do? This study addresses these questions, by focusing on a specific underlying neural mechanism involved in our visual experiences that affects our final perception. Among many types of visual illusion, 'Geometrical' and, in particular, 'Tilt Illusions' are rather important, being characterized by misperception of geometric patterns involving lines and tiles in combination with contrasting orientation, size or position. Over the last decade, many new neurophysiological experiments have led to new insights as to how, when and where retinal processing takes place, and the encoding nature of the retinal representation that is sent to the cortex for further processing. Based on these neurobiological discoveries, we provide computer simulation evidence from modelling retinal ganglion cells responses to some complex Tilt Illusions, suggesting that the emergence of tilt in these illusions is partially related to the interaction of multiscale visual processing performed in the retina. The output of our low-level filtering model is presented for several types of Tilt Illusion, predicting that the final tilt percept arises from multiple-scale processing of the Differences of Gaussians and the perceptual interaction of foreground and background elements. The model is a variation of classical receptive field implementation for simple cells in early stages of vision with the scales tuned to the object/texture sizes in the pattern. Our results suggest that this model has a high potential in revealing the underlying mechanism connecting low-level filtering approaches to mid- and high-level explanations such as 'Anchoring theory' and 'Perceptual grouping'.

Multiplicative and additive Adelson's snake illusions

Two different versions of Adelson's snake lightness illusion are quantitatively investigated. In one experiment an additive version of the illusion is investigated by varying the additive component of the atmosphere transfer function (ATF) introduced by Adelson [2000, in The New Cognitive Neuroscience Ed. M Gazzaniga (Cambridge, MA: MIT Press) pp 339-351]. In the other, a multiplicative version of the illusion is examined by varying the multiplicative component of the ATE In both experiments four observers matched the targets' lightness of the snake patterns with Munsell samples. Increasing the additive or the multiplicative component elicited an approximately equal increase in the magnitude of the lightness illusion. The results show that both components, in the absence of other kinds of information, can be used as heuristics by our visual system to anchor luminance of the object when converting it into lightness.

Effect of pictorial depth cues, binocular disparity cues and motion parallax depth cues on lightness perception in three-dimensional virtual scenes

Background

Surface lightness perception is affected by scene interpretation. There is some experimental evidence that perceived lightness under bi-ocular viewing conditions is different from perceived lightness in actual scenes but there are also reports that viewing conditions have little or no effect on perceived color. We investigated how mixes of depth cues affect perception of lightness in three-dimensional rendered scenes containing strong gradients of illumination in depth.

Methodology/Principal Findings

Observers viewed a virtual room (4 m width×5 m height×17.5 m depth) with checkerboard walls and floor. In four conditions, the room was presented with or without binocular disparity (BD) depth cues and with or without motion parallax (MP) depth cues. In all conditions, observers were asked to adjust the luminance of a comparison surface to match the lightness of test surfaces placed at seven different depths (8.5–17.5 m) in the scene. We estimated lightness versus depth profiles in all four depth cue conditions. Even when observers had only pictorial depth cues (no MP, no BD), they partially but significantly discounted the illumination gradient in judging lightness. Adding either MP or BD led to significantly greater discounting and both cues together produced the greatest discounting. The effects of MP and BD were approximately additive. BD had greater influence at near distances than far.

Conclusions/Significance

These results suggest the surface lightness perception is modulated by three-dimensional perception/interpretation using pictorial, binocular-disparity, and motion-parallax cues additively. We propose a two-stage (2D and 3D) processing model for lightness perception.

A fair test of the effect of a shadow-incompatible luminance gradient on the simultaneous lightness contrast

Shadow-compatibility of simultaneous lightness contrast is discussed by Alexander D Logvinenko and Paola Bressan, with examples claiming to provide a test of the hypothesis.

Does the bandpass linear filter response predict gradient lightness induction? A reply to Fred Kingdom

It is argued that lightness illusions induced by luminance gradient cannot be accounted for by the response of a bandpass linear filter as recently claimed by Kingdom (Perception 28 929-934).

Luminance gradient can break background-independent lightness constancy

A display with a luminance gradient was shown to induce a strong lightness illusion (Logvinenko, 1999 Perception 28 803-816). However, a 3-D cardboard model of this display was found to produce a much weaker illusion (less than half that in the pictorial version) despite the fact that its retinal image is practically the same. This is in line with the hypothesis that simultaneous lightness contrast is solely a phenomenon of pictorial perception (Logvinenko et al, 2002 Perception 31 73-82). The residual lightness illusion in the 3-D model can be accounted for by the fact that this model is a hybrid display. Specifically, while it is a real object, a pictorial representation (of the illumination gradient) is superimposed on it. Thus, lightness in the 3-D display is a compromise between two opposite tendencies: the background-independent lightness constancy and the lightness illusory shift induced by the luminance gradient.