Lightness and perceptual transparency

Brightness/darkness induction and the genesis of a contour

Visual contours often result from the integration or interpolation of fragmented edges. The strength of the completion increases when the edges share the same contrast polarity (CP). Here we demonstrate that the appearance in the perceptual field of this integrated unit, or contour of invariant CP, is concomitant with a vivid brightness alteration of the surfaces at its opposite sides. To observe this effect requires some stratagems because the formation in the visual field of a contour of invariant CP normally engenders the formation of a second contour and then the rise of two streams of induction signals that interfere in different ways. Particular configurations have been introduced that allow us to observe the induction effects of one contour taken in isolation. I documented these effects by phenomenological observations and psychophysical measurement of the brightness alteration in relation to luminance contrast. When the edges of the same CP complete to form a contour, the background of homogeneous luminance appears to dim at one side and to brighten at the opposite side (in accord with the CP). The strength of the phenomenon is proportional to the local luminance contrast. This effect weakens or nulls when the contour of the invariant CP separates surfaces filled with different gray shades. These conflicting results stimulate a deeper exploration of the induction phenomena and their role in the computation of brightness contrast. An alternative perspective is offered to account for some brightness illusions and their relation to the phenomenal transparency. The main assumption asserts that, when in the same region induction signals of opposite CP overlap, the filling-in is blocked unless the image is stratified into different layers, one for each signal of the same polarity. Phenomenological observations document this “solution” by the visual system.

The roles of image decomposition and edge curvature in the 'snake' lightness illusion

The snake illusion is an effect in which the lightness of target patches is strongly affected by the luminance of remote patches. One explanation is that such images are decomposed into a pattern of illumination and a pattern of reflectance, involving a classification of luminance edges into illumination and reflectance edges. Based on this decomposition, perceived reflectance is determined by discounting the illumination. A problem for this account is that image decomposition is not unique, and that different decompositions may lead to different lightness predictions. One way to rule out alternative decompositions and ensure correct predictions is to postulate that the visual system tends to classify curved luminance edges as reflectance edges rather than illumination edges. We have constructed several variations of the basic snake display in order to test the proposed curvature constraint and the more general image decomposition hypothesis. Although the results from some displays have confirmed previous findings of the effect of curvature, the general pattern of data questions the relevance of the shape of luminance edges for the determination of lightness in this class of displays. The data also argue against an image decomposition mechanism as an explanation of this effect. As an alternative, a tentative neurally based account is sketched.

Lightness, brightness and transparency: a quarter century of new ideas, captivating demonstrations and unrelenting controversy

The past quarter century has witnessed considerable advances in our understanding of Lightness (perceived reflectance), Brightness (perceived luminance) and perceived Transparency (LBT). This review poses eight major conceptual questions that have engaged researchers during this period, and considers to what extent they have been answered. The questions concern 1. the relationship between lightness, brightness and perceived non-uniform illumination, 2. the brain site for lightness and brightness perception, 3 the effects of context on lightness and brightness, 4. the relationship between brightness and contrast for simple patch-background stimuli, 5. brightness "filling-in", 6. lightness anchoring, 7. the conditions for perceptual transparency, and 8. the perceptual representation of transparency. The discussion of progress on major conceptual questions inevitably requires an evaluation of which approaches to LBT are likely and which are unlikely to bear fruit in the long term, and which issues remain unresolved. It is concluded that the most promising developments in LBT are (a) models of brightness coding based on multi-scale filtering combined with contrast normalization, (b) the idea that the visual system decomposes the image into "layers" of reflectance, illumination and transparency, (c) that an understanding of image statistics is important to an understanding of lightness errors, (d) Whittle's logW metric for contrast-brightness, (e) the idea that "filling-in" is mediated by low spatial frequencies rather than neural spreading, and (f) that there exist multiple cues for identifying non-uniform illumination and transparency. Unresolved issues include how relative lightness values are anchored to produce absolute lightness values, and the perceptual representation of transparency. Bridging the gap between multi-scale filtering and layer decomposition approaches to LBT is a major task for future research.

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.