Lightness and Junctions

Todorović, Dejan

doi:10.1068/p260379

Cited by 116 publications

(73 citation statements)

References 48 publications

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“…The results, however, should not be taken to imply that the visual system needs to group luminance patches into particular spatial arrangements to generate brightness, as has often been suggested (5)(6)(7)(8)(9)(10)(11). It should also be apparent from Fig.…”

Section: Resultsmentioning

confidence: 87%

“…1C). This failure has led to several more recent suggestions, including complex filtering and neural network models (3,4), the idea that brightness depends on detecting edges and junctions that promote the grouping of various luminances into interpretable spatial arrangements (5)(6)(7)(8)(9)(10)(11), and the proposal that brightness is ''resynthesized'' from 3D scene properties ''inferred'' from the stimulus (12)(13)(14). None of these approaches, however, can explain the full the range of brightness phenomena illustrated in Fig.…”

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confidence: 99%

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The statistical structure of natural light patterns determines perceived light intensity

Yang

Purves

2004

Proc. Natl. Acad. Sci. U.S.A.

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The same target luminance in different contexts can elicit markedly different perceptions of brightness, a fact that has long puzzled vision scientists. Here we test the proposal that the visual system encodes not luminance as such but rather the statistical relationship of a particular luminance to all possible luminance values experienced in natural contexts during evolution. This statistical conception of vision was validated by using a database of natural scenes in which we could determine the probability distribution functions of co-occurring target and contextual luminance values. The distribution functions obtained in this way predict target brightness in response to a variety of challenging stimuli, thus explaining these otherwise puzzling percepts. That brightness is determined by the statistics of natural light patterns implies that the relevant neural circuitry is specifically organized to generate these probabilistic responses. The perception elicited by the luminance of a visual target, generally called brightness, is arguably the most basic quality of vision. A central puzzle in understanding how such percepts are generated by the visual system is that brightness does not correspond in any simple way to luminance. Thus, the same amount of light arising from a given region in a scene can elicit dramatically different brightness percepts when presented in different contexts (1, 2) ( Fig. 1).A variety of explanations have been suggested since the basis for such phenomena was first debated by Helmholtz, Hering, Mach, and others. Although lateral inhibition in early visual processing has often been proposed to account for these ''illusions'' (1), this mechanism cannot explain instances in which similar overall contexts produce different brightness effects (compare Fig. 1 A with Figs. 1 B and E; see also Fig. 1C). This failure has led to several more recent suggestions, including complex filtering and neural network models (3, 4), the idea that brightness depends on detecting edges and junctions that promote the grouping of various luminances into interpretable spatial arrangements (5-11), and the proposal that brightness is ''resynthesized'' from 3D scene properties ''inferred'' from the stimulus (12)(13)(14). None of these approaches, however, can explain the full the range of brightness phenomena illustrated in Fig. 1 (1).Here we examine a different concept of the way brightness is generated by the visual system. A growing body of evidence has shown that the visual system uses the statistics of stimulus features in natural environments to generate the visual percepts of the physical world (15); if so, the visual system must incorporate these statistics as a central feature of processing relevant to brightness and other visual qualia (2). Accordingly, we suppose that the perceived brightness elicited by the luminance of a target in any given context is based on the value of the target luminance in the probability distribution function of the possible values that co-occur with that contextual luminance ...

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Section: Resultsmentioning

confidence: 87%

mentioning

confidence: 99%

The statistical structure of natural light patterns determines perceived light intensity

Yang

Purves

2004

Proc. Natl. Acad. Sci. U.S.A.

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“…Many studies, however, have documented the relative independence of lightness͞brightness and luminances as such. Matching studies, in particular, have shown that the same luminances can be made to look dramatically different by their context (12,(23)(24)(25)(26)(27)(28)(29)(30)(31)(32). Because in many instances the activity of visual neurons is correlated with perceptual qualities rather than the physical properties of the stimulus (in the case of brightness see refs.…”

Section: Discussionmentioning

confidence: 99%

A probabilistic explanation of brightness scaling

Nundy

Purves²

2002

Proc. Natl. Acad. Sci. U.S.A.

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The perceptions of lightness or brightness elicited by a visual target are linked to its luminance by a nonlinear function that varies according to the physical characteristics of the target and the background on which it is presented. Although no generally accepted explanation of this scaling relationship exists, it has long been considered a byproduct of low-or mid-level visual processing. Here we examine the possibility that brightness scaling is actually the signature of a biological strategy for dealing with inevitably ambiguous visual stimuli, in which percepts of lightness͞brightness are determined by the probabilistic relationship between luminances in the image plane and their possible real-world sources.lightness ͉ luminance ͉ context T he relationship between the physical intensity of a light stimulus and its subjective perception has been debated since at least the middle of the 19th century (1-3). The central problem in ongoing attempts to rationalize this linkage has been the variability between luminance (i.e., the intensity of the light returned to the eye from object surfaces or light sources) and the sense of lightness or brightness elicited by the stimulus. Although intuition suggests that these sensations should scale in direct proportion to the intensity of the light that activates retinal receptors, the intensity of the sensation varies in a manner that is difficult to rationalize (Fig. 1). Thus, when targets are presented as luminance increments relative to a given background luminance, the scaling relationship is a power function referred to as Stevens' Law. Despite the canonical implication, the exponent of this function varies widely according to the size of the target, the duration of its presentation, the nature of the source, and other experimental variables (2, 4). Moreover, the relationship changes markedly and systematically as function of the intensity of the background luminance (6, 7). Although no consensus exists about the basis of these phenomena, many authors have interpreted them as consequences of neural processing early in the visual pathway (8-10).Although these effects are certainly initiated by low-and midlevel neural processing, the observed peculiarities of scaling may signify an important purpose. The possibility that we examine here is that the relationship between luminance and the resulting perceptions of lightness or brightness reflects a probabilistic strategy of visual processing demanded by the inherent ambiguity of visual stimuli. In these terms, the perceived intensity of any luminant stimulus is determined by the probability distribution of the possible underlying sources, or, more precisely, by the probable contributions of reflectance (R) and illumination (I) to the luminances experienced in the past (11). The amount of light associated with any part of a scene-that is, its local luminance-is typically the product of the I of that region and the R efficiency function(s) of the relevant object surfaces (12). In consequence, an infinite set of possible com...

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“…The conclusion that the gray dots' lightnesses are perceived relative to the dots within their own group is consistent with an early grouping hypothesis, and it is sufficient to explain the observed contrast effect. There are quite a few such reports of strong and consistent grouping effects producing contrast phenomena that are otherwise difficult to explain (e.g., Adelson, 1993;Gilchrist, Kossyfidis, Bonato, & Agostini, 1999;Todorovic, 1997;White, 1979). Such effects are not definitive evidence that grouping occurs before constancy processing, however, because lightness contrast and lightness constancy are not the same process.…”

Section: Grouping and Lightness Constancymentioning

confidence: 99%