Inhomogeneous surrounds, conflicting frameworks, and the double-anchoring theory of lightness

Vertical anisotropy in lightness perception not caused by lighting assumption

Our recent study found an illusory effect whereby an image of an upward-facing gray panel appears darker than its 180-degree rotated image. We attributed this inversion effect to the observer's implicit assumption that light from above is more intense than light from below. This paper aims to explore the possibility that low-level visual anisotropy also contributes to the effect. In Experiment 1, we investigated whether the effect could be observed even when the position, the contrast polarity, and the existence of the edge were manipulated. In Experiments 2 and 3, the effect was further examined using stimuli that contained no depth cues. Experiment 4 confirmed the effect using stimuli of even simpler configuration. The results of all the experiments demonstrated that brighter edges on the upper side of the target make it appear lighter, indicating that low-level anisotropy contributes to the inversion effect, even without depth orientation information. However, darker edges on the upper side of the target produced ambiguous results. We speculate that the perceived lightness of the target might be affected by two kinds of vertical anisotropy, one of which is dependent on contrast polarity while the other is independent of it. Moreover, the results also replicated the previous finding that the lighting assumption contributes to perceived lightness. Overall, the present study demonstrates that both low-level vertical anisotropy and mid-level lighting assumption influence lightness.

An Upward-Facing Surface Appears Darker: The Role Played by the Light-From-Above Assumption in Lightness Perception

The human visual system can extract information on surface reflectance (lightness) from light intensity; this, however, confounds information on reflectance and illumination. We hypothesized that the visual system, to solve this lightness problem, utilizes the internally held prior assumption that illumination falls from above. Experiment 1 showed that an upward-facing surface is perceived to be darker than a downward-facing surface, proving our hypothesis. Experiment 2 showed the same results in the absence of explicit illumination cues. The effect of the light-from-left prior assumption was not observed in Experiment 3. The upward- and downward-facing surface stimuli in Experiments 1 and 2 showed no difference in a two-dimensional configuration or three-dimensional structure, and the participants' perceived lightness appeared to be affected by the observers' prior assumption that illumination is always from above. Other studies have not accounted for this illusory effect, and this study's finding provides additional insights into the study of lightness perception.

“Glowing Gray” Does Exist: Luminance Gradients’ Influence on Whiteness Perception

Studies on brightness and lightness that employed luminance gradients (i.e., glare stimuli) have suggested that we can perceive luminosity even when the brightness target is darker than white. Although such studies had great impact on research in luminosity perception, whether the whiteness threshold in glare stimuli was lower or higher than the luminosity threshold remained unclear. This study indicated that it is higher than the luminosity threshold, confirming the existence of glowing gray. Moreover, we measured the luminance gradients’ effect on whiteness perception but found no significant effect. Discrepancy in the degree of gradients’ effect on perceived luminosity and perceived white suggests that different mechanisms underlie luminosity (brightness) perception and whiteness (lightness) perception.

Luminance gradient configuration determines perceived lightness in a simple geometric illusion

Accurate perception of surface reflectance poses a significant computational problem for the visual system. The amount of light reflected by a surface is affected by a combination of factors including the surface's reflectance properties and illumination conditions. The latter are not limited by the strength of the illuminant but also include the relative placement of the light illuminating the surface, the orientation of the surface and its 3d shape, all of which result in a pattern of luminance gradients across the surface. In this study we explore how luminance gradients contribute to lightness perception. We introduce a novel, simple lightness illusion. It consists of six separate checks, organized in rows of two. Each check has a negative luminance gradient across it. The top and the bottom rows are the same: with the darker check on the left, and the lighter check on the right. Two checks in the middle row are identical; however, the check on the right appears darker than the check on the left. As there are no shared borders between the checks, simultaneous contrast cannot explain the effect. However, there are multiple possible explanations including spatial filtering (Blakeslee and McCourt, 2004) or some higher-order mechanism such as perceptual grouping or amodal completion. Here, we explore these possibilities by manipulating the luminance configurations and the gradient slopes of the checks.

Standard deviation of luminance distribution affects lightness and pupillary response

We examined whether the standard deviation (SD) of luminance distribution serves as information of illumination. We measured the lightness of a patch presented in the center of a scrambled-dot pattern while manipulating the SD of the luminance distribution. Results showed that lightness decreased as the SD of the surround stimulus increased. We also measured pupil diameter while viewing a similar stimulus. The pupil diameter decreased as the SD of luminance distribution of the stimuli increased. We confirmed that these results were not obtained because of the increase of the highest luminance in the stimulus. Furthermore, results of field measurements revealed a correlation between the SD of luminance distribution and illuminance in natural scenes. These results indicated that the visual system refers to the SD of the luminance distribution in the visual stimulus to estimate the scene illumination.

Clinical manifestations and trend of dengue cases admitted in a tertiary care hospital, udupi district, karnataka

Background:

India is one of the seven identified countries in the South-East Asia region regularly reporting dengue fever (DF)/dengue hemorrhagic fever (DHF) outbreaks and may soon transform into a major niche for dengue infection in the future with more and more new areas being struck by dengue epidemics

Objective:

To study the clinical manifestations, trend and outcome of all confirmed dengue cases admitted in a tertiary care hospital.

Study Design:

Record-based study conducted in a coastal district of Karnataka. Required data from all the laboratory confirmed cases from 2002 to 2008 were collected from Medical Records Department (MRD) and analyzed using SPSS 13.5 version.

Results:

Study included 466 patients. Majority were males, 301(64.6%) and in the and in the age group of 15-44 years, 267 (57.5%). Maximum number of cases were seen in 2007, 219 (47%) and in the month of September, 89 (19.1%). The most common presentation was fever 462 (99.1%), followed by myalgia 301 (64.6%), vomiting 222 (47.6%), headache 222 (47.6%) and abdominal pain 175 (37.6%). The most common hemorrhagic manifestation was petechiae 84 (67.2%). 391 (83.9%) cases presented with dengue fever, 41 (8.8%) dengue hemorrhagic fever, and 34 (7.3%) with dengue shock syndrome. Out of 66 (14.1%) patients who developed clinical complications, 22 (33.3%) had ARDS and 20 (30.3%) had pleural effusion. Deaths reported were 11(2.4%).

Conclusion:

Community awareness, early diagnosis and management and vector control measures need to be strengthened, during peri-monsoon period, in order to curb the increasing number of dengue cases.

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.

Linking depth to lightness and anchoring within the differentiation-integration formalism

Recently we developed a model that reproduces the Kanizsa square illusion based on two principles: (1) a spatial 2-D integration of luminance ratio and differentiated depth signals creates a "primary" lightness map and a depth map, respectively, which is then followed by (2) a modification of the primary lightness values under influence of the perceived depth (Kogo, Strecha, Van Gool, & Wagemans, 2010). Within this model, the process of the spatial integration inevitably introduced an arbitrary offset. In order to obtain absolute values of depth and lightness, the offset values needed to be determined by other constraints. This is the anchoring problem of the depth and lightness measurements. Here we report the anchoring rules that were established by investigating the model's responses to the Kanizsa square and its wide range of variations. For the primary lightness map, the highest value rule was applied, while the area rule appeared most plausible for the depth map. By applying the same principles to simple figures consisting of black and white areas of different size ratios, the model succeeded in reproducing published empirical results on lightness anchoring (Li & Gilchrist, 1999).

Paradoxical lightness contrast

The visual system's computation of lightness (perceived reflectance) leads to contrast effects in which a gray target region appears lighter on a black background than on a white one. Here we show a paradoxical contrast effect in which targets look lighter after adding regions that increase the scene's average luminance, and darker after adding regions that decrease this luminance. The paradoxical effect emerges if the target sits either on a black local background surrounded by a white remote background, or on a white local background surrounded by a black remote background. It does not occur if both backgrounds have the same luminance. The effect is consistent with Bressan's double-anchoring theory, and likely also with those edge-integration theories that assume gain control, but differs from previously reported effects of assimilation, articulation, reverse contrast, and remote contrast.

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.

Lightness of an object under two illumination levels

Anchoring theory (Gilchrist et al, 1999 Psychological Review 106 795-834) predicts a wide range of lightness errors, including failures of constancy in multi-illumination scenes and a long list of well-known lightness illusions seen under homogeneous illumination. Lightness values are computed both locally and globally and then averaged together. Local values are computed within a given region of homogeneous illumination. Thus, for an object that extends through two different illumination levels, anchoring theory produces two values, one for the patch in brighter illumination and one for the patch in dimmer illumination. Observers can give matches for these patches separately, but they can also give a single match for the whole object. Anchoring theory in its current form is unable to predict these object matches. We report eight experiments in which we studied the relationship between patch matches and object matches. The results show that the object match represents a compromise between the match for the patch in the field of highest illumination and the patch in the largest field of illumination. These two principles are parallel to the rules found for anchoring lightness: highest luminance rule and area rule.

Simultaneous lightness contrast on plain and articulated surrounds

Simultaneous lightness contrast is stronger when the dark and light backgrounds of the classic display (where one of the targets is an increment and the other is a decrement) are replaced by articulated fields of equivalent average luminances. Although routinely attributed to articulation per se, this effect may simply result from the increase in highest luminance in the light articulated, vs plain, background; by locally darkening the decremental target, such an increase would amplify the difference between the targets. We disentangled the effects of highest luminance and articulation by measuring, separately, the magnitude of lightness contrast on dark and light plain and articulated backgrounds. We found that highest luminance and articulation contribute separately to the final illusion.

The place of white in a world of grays: a double-anchoring theory of lightness perception

The specific gray shades in a visual scene can be derived from relative luminance values only when an anchoring rule is followed. The double-anchoring theory I propose in this article, as a development of the anchoring theory of Gilchrist et al. (1999), assumes that any given region (a) belongs to one or more frameworks, created by Gestalt grouping principles, and (b) is independently anchored, within each framework, to both the highest luminance and the surround luminance. The region's final lightness is a weighted average of the values computed, relative to both anchors, in all frameworks. The new model accounts not only for all lightness illusions that are qualitatively explained by the anchoring theory but also for a number of additional effects, and it does so quantitatively, with the support of mathematical simulations.