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

Iconic logic: the visual art of drawing the right conclusion

Most people, evidence suggests, have a hard time thinking straight. Symbolic logic is a tool that can help remedy this problem. Unfortunately, it is highly abstract and uses symbols whose meanings rely on unintuitive arbitrary conventions. Without sacrificing rigor, iconic logic is more concrete and uses icons that resemble what they stand for and whose meanings are thus easier to picture, process, and remember. Here I review and critique iconic existential graphs and concept diagrams-the former link iconic logic to iconic mathematics; the latter expand popular Euler or Venn diagrams and have, to some degree, been empirically investigated for user-friendliness. I lay out how expertise in perception, cognition, and genetics can inform and improve such empirical research to help make iconic logic more ergonomic. After all, logic is a tool, and tools should not only suit their use but also their user.

What Fechner could not do: Separating perceptual encoding and decoding with difference scaling

A key question in perception research is how stimulus variations translate into perceptual magnitudes, that is, the perceptual encoding process. As experimenters, we cannot probe perceptual magnitudes directly, but infer the encoding process from responses obtained in a psychophysical experiment. The most prominent experimental technique to measure perceptual appearance is matching, where observers adjust a probe stimulus to match a target in its appearance along the dimension of interest. The resulting data quantify the perceived magnitude of the target in physical units of the probe, and are thus an indirect expression of the underlying encoding process. In this paper, we show analytically and in simulation that data from matching tasks do not sufficiently constrain perceptual encoding functions, because there exist an infinite number of pairs of encoding functions that generate the same matching data. We use simulation to demonstrate that maximum likelihood conjoint measurement (Ho, Landy, & Maloney, 2008; Knoblauch & Maloney, 2012) does an excellent job of recovering the shape of ground truth encoding functions from data that were generated with these very functions. Finally, we measure perceptual scales and matching data for White's effect (White, 1979) and show that the matching data can be predicted from the estimated encoding functions, down to individual differences.

The Perceptual Science of Augmented Reality

Augmented reality (AR) systems aim to alter our view of the world and enable us to see things that are not actually there. The resulting discrepancy between perception and reality can create compelling entertainment and can support innovative approaches to education, guidance, and assistive tools. However, building an AR system that effectively integrates with our natural visual experience is hard. AR systems often suffer from visual limitations and artifacts, and addressing these flaws requires basic knowledge of perception. At the same time, AR system development can serve as a catalyst that drives innovative new research in perceptual science. This review describes recent perceptual research pertinent to and driven by modern AR systems, with the goal of highlighting thought-provoking areas of inquiry and open questions.

Isolation of brightness induction effects on target patches from adjacent surrounds and remote backgrounds

The brightness (perceived intensity) of a region of visual space depends on its luminance and on the luminance of nearby regions. This phenomenon is called brightness induction and includes both brightness contrast and assimilation. Historically, and on a purely descriptive level, brightness contrast refers to a directional shift in target brightness away from the brightness of an adjacent region while assimilation refers to a brightness shift toward that of an adjacent region. In order to understand mechanisms, it is important to differentiate the descriptive terms contrast and assimilation from the optical and/or neural processes, often similarly named, which cause the effects. Experiment 1 isolated the effect on target patch (64 cd/m2) matching luminance (brightness) of six surround-ring widths (0.1°–24.5°) varied over 11 surround-ring luminances (32–96 cd/m2). Using the same observers, Experiment 2 examined the effect of the identical surround-ring parameters on target patch matching luminance in the presence of a dark (0.0 cd/m2) and a bright (96 cd/m2) remote background. By differencing the results of Experiment 1 (the isolated effect of the surround-ring) from those of Experiment 2 (the combined effect of the surround-ring with the dark and bright remote background) we further isolated the effect of the remote background. The results reveal that surround-rings and remote backgrounds produce brightness contrast effects in the target patch that are of the same or opposite polarity depending on the luminance polarity of these regions relative to target patch luminance. The strength of brightness contrast from the surround-ring varied with surround-ring luminance and width. Brightness contrast (darkening) in the target from the bright remote background was relatively constant in magnitude across all surround-ring luminances and increased in magnitude with decreasing surround-ring width. Brightness contrast (brightening) from the isolated dark remote background also increased in magnitude with decreasing surround-ring width: however, despite some regional flattening of the functions due to the fixed luminance of the dark remote background, induction magnitude was much reduced in the presence of a surround-ring of greater luminance than the target patch indicating a non-linear interaction between the dark remote background and surround-ring luminance.

On the synthesis of visual illusions using deep generative models

Visual illusions expand our understanding of the visual system by imposing constraints in the models in two different ways: i) visual illusions for humans should induce equivalent illusions in the model, and ii) illusions synthesized from the model should be compelling for human viewers too. These constraints are alternative strategies to find good vision models. Following the first research strategy, recent studies have shown that artificial neural network architectures also have human-like illusory percepts when stimulated with classical hand-crafted stimuli designed to fool humans. In this work we focus on the second (less explored) strategy: we propose a framework to synthesize new visual illusions using the optimization abilities of current automatic differentiation techniques. The proposed framework can be used with classical vision models as well as with more recent artificial neural network architectures. This framework, validated by psychophysical experiments, can be used to study the difference between a vision model and the actual human perception and to optimize the vision model to decrease this difference.

Simple Assumptions to Improve Markov Illuminance and Reflectance

Murray recently introduced a novel computational lightness model, Markov illuminance and reflectance (MIR). MIR is a promising new approach that simulates human lightness processing using a conditional random field (CRF) where natural-scene statistics of reflectance and illumination are implemented. Although MIR can account for various lightness illusions and phenomena, it has limitations, such as the inability to predict reverse-contrast phenomena. In this study, we improved MIR performance by modifying its inference process, the prior on X-junctions, and that on general illumination changes. Our modified model improved predictions for Checkerboard assimilation, the simplified Checkershadow and its control figure, the influence of luminance noise, and White's effect and its several variants. In particular, White's effect is a partial reverse contrast that is challenging for computational models, so this improvement is a significant advance for the MIR framework. This study showed the high extensibility and potential of MIR, which shows the promise for further sophistication.

Equivalent noise characterization of human lightness constancy

A goal of visual perception is to provide stable representations of task-relevant scene properties (e.g. object reflectance) despite variation in task-irrelevant scene properties (e.g. illumination and reflectance of other nearby objects). To study such stability in the context of the perceptual representation of lightness, we introduce a threshold-based psychophysical paradigm. We measure how thresholds for discriminating the achromatic reflectance of a target object (task-relevant property) in rendered naturalistic scenes are impacted by variation in the reflectance functions of background objects (task-irrelevant property), using a two-alternative forced-choice paradigm in which the reflectance of the background objects is randomized across the two intervals of each trial. We control the amount of background reflectance variation by manipulating a statistical model of naturally occurring surface reflectances. For low background object reflectance variation, discrimination thresholds were nearly constant, indicating that observers’ internal noise determines threshold in this regime. As background object reflectance variation increases, its effects start to dominate performance. A model based on signal detection theory allows us to express the effects of task-irrelevant variation in terms of the equivalent noise, that is relative to the intrinsic precision of the task-relevant perceptual representation. The results indicate that although naturally occurring background object reflectance variation does intrude on the perceptual representation of target object lightness, the effect is modest – within a factor of two of the equivalent noise level set by internal noise.

Conjoint measurement of perceived transparency and perceived contrast in variegated checkerboards

One fundamental question in vision research is how the retinal input is segmented into perceptually relevant variables. A striking example of this segmentation process is transparency perception, in which luminance information in one location contributes to two perceptual variables: the properties of the transparent medium itself and of what is being seen in the background. Previous work by Robilotto et al. (2002, 2004) suggested that perceived transparency is closely related to perceived contrast, but how these two relate to retinal luminance has not been established. Here we studied the relationship between perceived transparency, perceived contrast, and image luminance using maximum likelihood conjoint measurement (MLCM). Stimuli were rendered images of variegated checkerboards that were composed of multiple reflectances and partially covered by a transparent overlay. We systematically varied the transmittance and reflectance of the transparent medium and measured perceptual scales of perceived transparency. We also measured scales of perceived contrast using cut-outs of the transparency stimuli that did not contain any geometrical cues to transparency. Perceptual scales for perceived transparency and contrast followed a remarkably similar pattern across observers. We tested the empirically observed scales against predictions from various contrast metrics and found that perceived transparency and perceived contrast were equally well predicted by a metric based on the logarithm of Michelson or Whittle contrast. We conclude that judgments of perceived transparency and perceived contrast are likely to be supported by a common mechanism, which can be computationally captured as a logarithmic contrast.

Behavioural and electrophysiological correlates of lightness contrast and assimilation

Lightness contrast and assimilation are opposite phenomena: in contrast grey targets appear darker when bordering bright rather than dark surfaces; in assimilation grey targets appear lighter when bordering bright rather than dark surfaces. The underlying neurophysiological mechanisms of these phenomena are not known. The aim of this study was to investigate the relationship between contrast and assimilation, and the timing and levels of perceptual and cognitive processing using combined behavioural and electrophysiological methods. Thirty undergraduate students (23 female, age range 18–48 years) participated in a forced-choice (grey target is lighter/darker than a comparison square) task, using stimuli designed such that the inducers were in two configurations (small and large) and two shades (white and black). The behavioural data (more consistent and faster responses) corroborated previous findings of stronger contrast effects with white inducers and stronger assimilation effects with black inducers. According to the Event-Related Potentials (ERP) results the mean amplitude was larger in conditions with less consistent and slower behavioural responses. Thus, with contrast responses P1 amplitude was larger with black than white inducers, and N1 amplitude was larger to assimilation than contrast when the configuration of the stimulus was held constant. These results suggest contrast may occur as early as P1 (~ 110 ms) and assimilation may occur later in N2 (~ 220 ms), whereas in some conditions, differences in ERPs associated with contrast vs assimilation may happen as early as in N1 (~ 170 m), in occipital and parietal cortical sites.

Lightness Perception in Complex Scenes

Lightness perception is the perception of achromatic surface colors: black, white, and shades of grey. Lightness has long been a central research topic in experimental psychology, as perceiving surface color is an important visual task but also a difficult one due to the deep ambiguity of retinal images. In this article, I review psychophysical work on lightness perception in complex scenes over the past 20 years, with an emphasis on work that supports the development of computational models. I discuss Bayesian models, equivalent illumination models, multidimensional scaling, anchoring theory, spatial filtering models, natural scene statistics, and related work in computer vision. I review open topics in lightness perception that seem ready for progress, including the relationship between lightness and brightness, and developing more sophisticated computational models of lightness in complex scenes. Expected final online publication date for the Annual Review of Vision Science, Volume 7 is September 2021. Please see http://www.annualreviews.org/page/journal/pubdates for revised estimates.

Matching visual induction effects on screens of different size

In the film industry, the same movie is expected to be watched on displays of vastly different sizes, from cinema screens to mobile phones. But visual induction, the perceptual phenomenon by which the appearance of a scene region is affected by its surroundings, will be different for the same image shown on two displays of different dimensions. This phenomenon presents a practical challenge for the preservation of the artistic intentions of filmmakers, because it can lead to shifts in image appearance between viewing destinations. In this work, we show that a neural field model based on the efficient representation principle is able to predict induction effects and how, by regularizing its associated energy functional, the model is still able to represent induction but is now invertible. From this finding, we propose a method to preprocess an image in a screen-size dependent way so that its perception, in terms of visual induction, may remain constant across displays of different size. The potential of the method is demonstrated through psychophysical experiments on synthetic images and qualitative examples on natural images.

Infants recognize words spoken through opaque masks but not through clear masks

COVID-19 has modified numerous aspects of children's social environments. Many children are now spoken to through a mask. There is little empirical evidence attesting to the effects of masked language input on language processing. In addition, not much is known about the effects of clear masks (i.e., transparent face shields) versus opaque masks on language comprehension in children. In the current study, 2-year-old infants were tested on their ability to recognize familiar spoken words in three conditions: words presented with no mask, words presented through a clear mask, and words presented through an opaque mask. Infants were able to recognize familiar words presented without a mask and when hearing words through opaque masks, but not when hearing words through clear masks. Findings suggest that the ability of infants to recover spoken language input through masks varies depending on the surface properties of the mask.

Ten seconds of my nights: Exploring methods to measure brightness, loudness and attendance and their associations with alcohol use from video clips

Introduction

Most evidence on associations between alcohol use behaviors and the characteristics of its social and physical context is based on self-reports from study participants and, thus, only account for their subjective impressions of the situation. This study explores the feasibility of obtaining alternative measures of loudness, brightness, and attendance (number of people) using 10-second video clips of real-life drinking occasions rated by human annotators and computer algorithms, and explores the associations of these measures with participants’ choice to drink alcohol or not.

Methods

Using a custom-built smartphone application, 215 16-25-year-olds documented characteristics of 2,380 weekend night drinking events using questionnaires and videos. Ratings of loudness, brightness, and attendance were obtained from three sources, namely in-situ participants’ ratings, video-based annotator ratings, and video-based computer algorithm ratings. Bivariate statistics explored differences in ratings across sources. Multilevel logistic regressions assessed the associations of contextual characteristics with alcohol use. Finally, model fit indices and cross-validation were used to assess the ability of each set of contextual measures to predict participants’ alcohol use.

Results

Raw ratings of brightness, loudness and attendance differed slightly across sources, but were all correlated (r = .21 to .82, all p < .001). Participants rated bars/pubs as being louder (Cohen’s d = 0.50 [95%-CI: 0.07–0.92]), and annotators rated private places as darker (d = 1.21 [95%-CI: 0.99–1.43]) when alcohol was consumed than when alcohol was not consumed. Multilevel logistic regressions showed that drinking in private places was more likely in louder (OR_participants = 1.74 [CI: 1.31–2.32]; OR_annotators = 3.22 [CI: 2.06–5.03]; OR_algorithm = 2.62 [CI: 1.83–3.76]), more attended (OR_participants = 1.10 [CI: 1.03–1.18]; OR_algorithm = 1.19 [CI: 1.07–1.32]) and darker (OR = 0.64 [CI: 0.44–0.94]) situations. In commercial venues, drinking was more likely in darker (OR_participants = 0.67 [CI: 0.47–0.94]; OR_annotators = 0.53 [CI: 0.33–0.85]; OR_algorithm = 0.58 [CI: 0.37–0.88]) and louder (OR_participants = 1.40 [CI: 1.02–1.92]; OR_algorithm = 2.45 [CI: 1.25–4.80]) places. Higher inference accuracies were found for the models based on the annotators’ ratings (80% to 84%) and the algorithms’ ratings (76% to 86%) than on the participants’ ratings (69% to 71%).

Conclusions

Several contextual characteristics are associated with increased odds of drinking in private and commercial settings, and might serve as a basis for the development of prevention measures. Regarding assessment of contextual characteristics, annotators and algorithms might serve as appropriate substitutes of participants’ in-situ impressions for correlational and regression analyses despite differences in raw ratings. Collecting contextual data by means of sensors or media files is recommended for future research.

Dynamic decorrelation as a unifying principle for explaining a broad range of brightness phenomena

The visual system is highly sensitive to spatial context for encoding luminance patterns. Context sensitivity inspired the proposal of many neural mechanisms for explaining the perception of luminance (brightness). Here we propose a novel computational model for estimating the brightness of many visual illusions. We hypothesize that many aspects of brightness can be explained by a dynamic filtering process that reduces the redundancy in edge representations on the one hand, while non-redundant activity is enhanced on the other. The dynamic filter is learned for each input image and implements context sensitivity. Dynamic filtering is applied to the responses of (model) complex cells in order to build a gain control map. The gain control map then acts on simple cell responses before they are used to create a brightness map via activity propagation. Our approach is successful in predicting many challenging visual illusions, including contrast effects, assimilation, and reverse contrast with the same set of model parameters.

Brightness matching in optical see-through augmented reality

A visual experiment using a beam-splitter-based optical see-through augmented reality (OST-AR) setup tested the effect of the size and alignment of AR overlays with a brightness-matching task using physical cubes. Results indicate that more luminance is required when AR overlays are oversized with respect to the cubes, showing that observers discount the AR overlay to a greater extent when it is more obviously a transparent layer. This is not explained by conventional color appearance modeling but supports an AR-specific model based on foreground-background discounting. The findings and model will help determine parameters for creating convincing AR manipulation of real-world objects.

What Are Visual Illusions?

Visual illusions have been a popular topic of study for a long time, but in recent years, a number of authors have questioned the coherence of this notion. This article deals in depth with ways in which illusions have been, could be, and should be defined and with various criticisms and different conceptions of the notion of illusions. After a review of definitions of illusions in the relevant literature, a more comprehensive but also more restrictive framework is presented, involving both veridicality and illusoriness, and is illustrated using two variants of a 2 × 2 scheme for the presentation of illusions. Many different aspects of illusions are discussed. A set of criteria for illusionhood is listed. Criticisms of the notion of illusions are presented, commented upon, and responded to. Conceptions of illusions differing from the one advocated here are discussed. Throughout the paper, novel variations of illusions are shown, and problems with accounts of some well-known illusions are noted. Examples of strong context effects which are not considered to be illusions are presented. It is concluded that the notion of visual illusions, suitably reformulated, is still viable.

Infants distinguish and represent pattern as an object feature from externally generated patterns superimposed on real, 3-dimensional objects' surfaces

As infants form object representations, the patterns viewed on objects' surfaces may be challenging to decipher because these patterns may be created from the surface reflectance of an object (an object property) or from an external source, such as a cast shadow. We tested 7 ½-month-old infants' use of cues that specify the source of patterns seen on the surfaces of real, 3-dimensional objects to individuate those objects. Results suggest that when forming object representations based on patterns, 7½-month-olds rely heavily on temporal and depth cues to distinguish patterns inherent to the object from other types of patterns.

More than noise: context-dependent luminance contrast discrimination in a coral reef fish (Rhinecanthus aculeatus)

Achromatic (luminance) vision is used by animals to perceive motion, pattern, space and texture. Luminance contrast sensitivity thresholds are often poorly characterised for individual species and are applied across a diverse range of perceptual contexts using over-simplified assumptions of an animal's visual system. Such thresholds are often estimated using the receptor noise limited model (RNL). However, the suitability of the RNL model to describe luminance contrast perception remains poorly tested. Here, we investigated context-dependent luminance discrimination using triggerfish (Rhinecanthus aculeatus) presented with large achromatic stimuli (spots) against uniform achromatic backgrounds of varying absolute and relative contrasts. 'Dark' and 'bright' spots were presented against relatively dark and bright backgrounds. We found significant differences in luminance discrimination thresholds across treatments. When measured using Michelson contrast, thresholds for bright spots on a bright background were significantly higher than for other scenarios, and the lowest threshold was found when dark spots were presented on dark backgrounds. Thresholds expressed in Weber contrast revealed lower thresholds for spots darker than their backgrounds, which is consistent with the literature. The RNL model was unable to estimate threshold scaling across scenarios as predicted by the Weber-Fechner law, highlighting limitations in the current use of the RNL model to quantify luminance contrast perception. Our study confirms that luminance contrast discrimination thresholds are context dependent and should therefore be interpreted with caution.

The perception threshold of the panda illusion, a particular form of 2D pulse-width-modulated halftone, correlates with visual acuity

To call attention to the danger of extinction of the panda bear, the Lithuanian artist Ilja Klemencov created the artwork “They can disappear”. The illustration is composed of black-and-white zigzagged lines, which form the famous panda logo of the World Wild Fund For Nature (WWF) when seen from a distance. If one is too close to the artwork, it is difficult to spot the bear, however, if one steps back or takes off one’s glasses the panda suddenly appears. This led us to ask if the ability to see the panda is related to the visual acuity of the observer and if therefore, the panda illusion can be used to assess the spatial resolution of the eye. Here we present the results of the comparison between visual acuity determined using the Landolt C and that predicted from the panda illusion in 23 healthy volunteers with artificially reduced visual acuity. Furthermore, we demonstrate that the panda illusion is based on a 2D pulse-width modulation, explain its technical history, and provide the equations required to create the illusion. Finally, we explain why the illusion indeed can be used to predict visual acuity and discuss the neural causes of its perception with best-corrected visual acuity.

A model of lightness perception guided by probabilistic assumptions about lighting and reflectance

Lightness perception is the ability to perceive black, white, and gray surface colors in a wide range of lighting conditions and contexts. This ability is fundamental for any biological or artificial visual system, but it poses a difficult computational problem, and how the human visual system computes lightness is not well understood. Here I show that several key phenomena in lightness perception can be explained by a probabilistic graphical model that makes a few simple assumptions about local patterns of lighting and reflectance, and infers globally optimal interpretations of stimulus images. Like human observers, the model exhibits partial lightness constancy, codetermination, contrast, glow, and articulation effects. It also arrives at human-like interpretations of strong lightness illusions that have challenged previous models. The model's assumptions are reasonable and generic, including, for example, that lighting intensity spans a much wider range than surface reflectance and that shadow boundaries tend to be straighter than reflectance edges. Thus, a probabilistic model based on simple assumptions about lighting and reflectance gives a good computational account of lightness perception over a wide range of conditions. This work also shows how graphical models can be extended to develop more powerful models of constancy that incorporate features such color and depth.

In vivo magnetic resonance imaging of orthotopic prostate cancer

Methods for imaging orthotopic prostate tumors within the prostate or small tumors with extension outside the prostate are needed to more closely model human prostate tumors, which are most commonly located within the gland or may extend just through the gland. By comparing MR sequences, we found that the T2-based Dixon 'water only' sequence best visualized tumors within the prostate of mouse models in both young and old mice and that tumor weight derived from this sequence correlated highly with ex vivo tumor weight (r² = 0.98, p < 0.001, n = 12). This should aid tumor detection, margin delineation and evaluation of tumor burden to enable studies including, but not limited to, evaluating the natural history of the disease, the mechanisms of action and the efficacy of therapeutic interventions.

Transparent layer constancy is improved by motion, stereo disparity, highly regular background pattern, and successive presentation

The visual system uses figural and colorimetric regularities in the retinal image to recognize optical filters and to discern the properties of the transparent overlay from properties of the background. Previous work suggests that the perceived color and transmittance of the transparent layer vary less under illumination changes than it would be expected from corresponding changes in the input. Here, we tested how the degree of this approximate transparent layer constancy (TLC) depends on factors that presumably facilitate the decomposition into a filter and a background layer. Using an asymmetric filter matching task, we found that motion, stereo disparity, and a highly regular background pattern each contribute to the vividness of the transparency impression and the degree of TLC. Combining these cues led to a cumulative increase in TLC, suggesting a "strong fusion" cue integration process. We also tested objects with invalid figural conditions for transparency (T-junctions). The tendency to perceive these objects as opaque and to establish a proximal match increased the more conspicuous the violation of this figural condition was. Furthermore, we investigated the gain in TLC due to alternating presentation. Alternating presentation enhanced TLC and color constancy to a comparable degree, and our results suggest that adaptation contributes to this effect.

Visual illusions via neural dynamics: Wilson-Cowan-type models and the efficient representation principle

We reproduce suprathreshold perception phenomena, specifically visual illusions, by Wilson-Cowan (WC)-type models of neuronal dynamics. Our findings show that the ability to replicate the illusions considered is related to how well the neural activity equations comply with the efficient representation principle. Our first contribution consists in showing that the WC equations can reproduce a number of brightness and orientation-dependent illusions. Then we formally prove that there cannot be an energy functional that the WC dynamics are minimizing. This leads us to consider an alternative, variational modeling, which has been previously employed for local histogram equalization (LHE) tasks. To adapt our model to the architecture of V1, we perform an extension that has an explicit dependence on local image orientation. Finally, we report several numerical experiments showing that LHE provides a better reproduction of visual illusions than the original WC formulation, and that its cortical extension is capable also to reproduce complex orientation-dependent illusions.NEW & NOTEWORTHY We show that the Wilson-Cowan equations can reproduce a number of brightness and orientation-dependent illusions. Then we formally prove that there cannot be an energy functional that the Wilson-Cowan equations are minimizing, making them suboptimal with respect to the efficient representation principle. We thus propose a slight modification that is consistent with such principle and show that this provides a better reproduction of visual illusions than the original Wilson-Cowan formulation. We also consider the cortical extension of both models to deal with more complex orientation-dependent illusions.

Luminance potentiates human visuocortical responses

Our visual system is tasked with transforming variations in light within our environment into a coherent percept, typically described using properties such as luminance and contrast. Models of vision often downplay the importance of luminance in shaping cortical responses, instead prioritizing representations that do not covary with overall luminance (i.e., contrast), and yet visuocortical response properties that may reflect luminance encoding remain poorly understood. In this study, we examined whether well-established visuocortical response properties may also reflect luminance encoding, challenging the idea that luminance information itself plays no significant role in supporting visual perception. To do so, we measured functional activity in human visual cortex when presenting stimuli varying in contrast and mean luminance, and found that luminance response functions are strongly contrast dependent between 50 and 250 cd/m², confirmed with a subsequent experiment. High-contrast stimuli produced linearly increasing responses as luminance increased logarithmically for all early visual areas, whereas low-contrast stimuli produced either flat (V1) or assorted positive linear (V2 and V3) response profiles. These results reveal that the mean luminance information of a visual signal persists within visuocortical representations, potentially reflecting an inherent imbalance of excitatory and inhibitory components that can be either contrast dependent (V1 and V2) or contrast invariant (V3). The role of luminance should be considered when the aim is to drive potent visually evoked responses and when activity is compared across studies. More broadly, overall luminance should be weighed heavily as a core feature of the visual system and should play a significant role in cortical models of vision.NEW & NOTEWORTHY This neuroimaging study investigates the influence of overall luminance on population activity in human visual cortex. We discovered that the response to a particular stimulus contrast level is reliant, in part, on the mean luminance of a signal, revealing that the mean luminance information of our environment is represented within the visual cortex. The results challenge a long-standing misconception about the role of luminance information in the processing of visual information at the cortical level.

CIE self-luminous gray-scale calculation: inflections, parameters, and high-contrast limiting behavior

Wide generalizability of the CIE-recommended gray-scale calculation for self-luminous devices suggests that its parameters, the extrema of the calculation's derivatives, and its limiting behavior are fundamental. The calculation has a negative-contrast point of inflection that is not predicted by any other gray-scale calculation, but that is consistent with data and with the terrestrial luminance histogram. The parameters of the calculation are analyzed, and their significance is explained. High-positive-contrast behavior of the calculation is shown and related to scientific literature. This knowledge represents a clearer understanding of daylight suprathreshold vision, and it enables optimal luminance-coding of contemporary high-resolution, high-contrast, high-luminance displays.

Neighboring chromaticity influences how white a surface looks

To identify surface properties independently of the illumination the visual system must make assumptions about the statistics of scenes and their illumination. Are assumptions about the intensity of the illumination independent of assumptions about its chromaticity? To find out, we asked participants to judge whether test patches within three different sets of surrounding surfaces were white or grey. Two sets were matched in terms of their maximal luminance, their mean luminance and chromaticity, and the variability in their luminance and chromaticity, but differed in how luminance and chromaticity were associated: the highest luminance was either associated with colorful surfaces or with achromatic ones. We found that test patches had to have a higher luminance to appear white when the highest luminance in the surrounding was associated with colorful surfaces. This makes sense if one considers that being colorful implies that a surface only reflects part of the light that falls on it, meaning that the illumination must have a higher luminance (a perfectly white surface reflects all of the light falling on it). In the third set, the colorful surfaces had the same luminance as in the set in which they were associated with the highest luminance, but the achromatic surfaces had a lower luminance so that the overall mean luminance was lower. Despite the constraints on the illumination being identical, test patches did not have to have as high luminance to appear white for the third set. Considering the layout of the surfaces in the surrounding revealed that test patches did have to have the same high luminance if the high luminance colorful surfaces were adjacent to the target patch. Thus, the assumptions about the possible illumination are applied locally. A possible mechanism is relying on the contrast within each type of cone: for a surface to appear white it must stimulate each of the three kinds of cones substantially more than do any neighboring surfaces.

Light: Toward a Transdisciplinary Science of Appearance and Atmosphere

To understand the processes behind seeing light, we need to integrate knowledge about the incoming optical structure, its perception, and how light interacts with material, shape, and space-objectively and subjectively. To that end, we need a novel approach to the science of light, namely, a transdisciplinary science of appearance, integrating optical, perceptual, and design knowledge and methods. In this article, I review existing literature as a basis for such a synthesis, which should discuss light in its full complexity, including its spatial properties and interactions with materials, shape, and space. I propose to investigate this by representing the endless variety of light, materials, shapes, and space as canonical modes and their combinations.

Cuttlefish: Color Mapping for Dynamic Multi-Scale Visualizations

Visualizations of hierarchical data can often be explored interactively. For example, in geographic visualization, there are continents, which can be subdivided into countries, states, counties and cities. Similarly, in models of viruses or bacteria at the highest level are the compartments, and below that are macromolecules, secondary structures (such as α-helices), amino-acids, and on the finest level atoms. Distinguishing between items can be assisted through the use of color at all levels. However, currently, there are no hierarchical and adaptive color mapping techniques for very large multi-scale visualizations that can be explored interactively. We present a novel, multi-scale, color-mapping technique for adaptively adjusting the color scheme to the current view and scale. Color is treated as a resource and is smoothly redistributed. The distribution adjusts to the scale of the currently observed detail and maximizes the color range utilization given current viewing requirements. Thus, we ensure that the user is able to distinguish items on any level, even if the color is not constant for a particular feature. The coloring technique is demonstrated for a political map and a mesoscale structural model of HIV. The technique has been tested by users with expertise in structural biology and was overall well received.

Layer and framework theories of lightness

Lightness (the perceived dimension running from black to white) represents a problem for vision science because the light coming to the eye from an object totally fails to specify the shade of gray of the object, due to the confounding of surface gray and illumination intensity. The two leading approaches, decomposition theories and anchoring theories, split the retinal image into overlapping layers and adjacent frameworks, respectively. Because each approach has important strengths and some weaknesses, an integration of them would mark an important step forward for the lightness theory. But the problem remains how this integration can actually be realized.

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.

Seeing through transparent layers

The human visual system is remarkably good at decomposing local and global deformations in the flow of visual information into different perceptual layers, a critical ability for daily tasks such as driving through rain or fog or catching that evasive trout. In these scenarios, changes in the visual information might be due to a deforming object or deformations due to a transparent medium, such as structured glass or water, or a combination of these. How does the visual system use image deformations to make sense of layering due to transparent materials? We used eidolons to investigate equivalence classes for perceptually similar transparent layers. We created a stimulus space for perceptual equivalents of a fiducial scene by systematically varying the local disarray parameters reach and grain. This disarray in eidolon space leads to distinct impressions of transparency, specifically, high reach and grain values vividly resemble water whereas smaller grain values appear diffuse like structured glass. We asked observers to adjust image deformations so that the objects in the scene looked like they were seen (a) under water, (b) behind haze, or (c) behind structured glass. Observers adjusted image deformation parameters by moving the mouse horizontally (grain) and vertically (reach). For two conditions, water and glass, we observed high intraobserver consistency: responses were not random. Responses yielded a concentrated equivalence class for water and structured glass.

A Compound Computational Model for Filling-In Processes Triggered by Edges: Watercolor Illusions

The goal of our research was to develop a compound computational model with the ability to predict different variations of the “watercolor effects” and additional filling-in effects that are triggered by edges. The model is based on a filling-in mechanism solved by a Poisson equation, which considers the different gradients as “heat sources” after the gradients modification. The biased (modified) contours (edges) are ranked and determined according to their dominancy across the different chromatic and achromatic channels. The color and intensity of the perceived surface are calculated through a diffusive filling-in process of color triggered by the enhanced and biased edges of stimulus formed as a result of oriented double-opponent receptive fields. The model can successfully predict both the assimilative and non-assimilative watercolor effects, as well as a number of “conflicting” visual effects. Furthermore, the model can also predict the classic Craik–O'Brien–Cornsweet (COC) effect. In summary, our proposed computational model is able to predict most of the “conflicting” filling-in effects that derive from edges that have been recently described in the literature, and thus supports the theory that a shared visual mechanism is responsible for the vast variety of the “conflicting” filling-in effects that derive from edges.

Computational luminance constancy from naturalistic images

The human visual system supports stable percepts of object color even though the light that reflects from object surfaces varies significantly with the scene illumination. To understand the computations that support stable color perception, we study how estimating a target object's luminous reflectance factor (LRF; a measure of the light reflected from the object under a standard illuminant) depends on variation in key properties of naturalistic scenes. Specifically, we study how variation in target object reflectance, illumination spectra, and the reflectance of background objects in a scene impact estimation of a target object's LRF. To do this, we applied supervised statistical learning methods to the simulated excitations of human cone photoreceptors, obtained from labeled naturalistic images. The naturalistic images were rendered with computer graphics. The illumination spectra of the light sources and the reflectance spectra of the surfaces in the scene were generated using statistical models of natural spectral variation. Optimally decoding target object LRF from the responses of a small learned set of task-specific linear receptive fields that operate on a contrast representation of the cone excitations yields estimates that are within 13% of the correct LRF. Our work provides a framework for evaluating how different sources of scene variability limit performance on luminance constancy.

Neuronal population mechanisms of lightness perception

The way that humans and animals perceive the lightness of an object depends on its physical luminance as well as its surrounding context. While neuronal responses throughout the visual pathway are modulated by context, the relationship between neuronal responses and lightness perception is poorly understood. We searched for a neuronal mechanism of lightness by recording responses of neuronal populations in monkey primary visual cortex (V1) and area V4 to stimuli that produce a lightness illusion in humans, in which the lightness of a disk depends on the context in which it is embedded. We found that the way individual units encode the luminance (or equivalently for our stimuli, contrast) of the disk and its context is extremely heterogeneous. This motivated us to ask whether the population representation in either V1 or V4 satisfies three criteria: 1) disk luminance is represented with high fidelity, 2) the context surrounding the disk is also represented, and 3) the representations of disk luminance and context interact to create a representation of lightness that depends on these factors in a manner consistent with human psychophysical judgments of disk lightness. We found that populations of units in both V1 and V4 fulfill the first two criteria but that we cannot conclude that the two types of information in either area interact in a manner that clearly predicts human psychophysical measurements: the interpretation of our population measurements depends on how subsequent areas read out lightness from the population responses. NEW & NOTEWORTHY A core question in visual neuroscience is how the brain extracts stable representations of object properties from the retinal image. We searched for a neuronal mechanism of lightness perception by determining whether the responses of neuronal populations in primary visual cortex and area V4 could account for a lightness illusion measured using human psychophysics. Our results suggest that comparing psychophysics with population recordings will yield insight into neuronal mechanisms underlying a variety of perceptual phenomena.

Suprathreshold gray scale is implied by thresholds

The inverse of the threshold just noticeable difference (i.e., 1/JND) is proportional to the slope (derivative with respect to visual stimulus luminance) of the suprathreshold gray scale at any stimulus and background luminances. Specifically, the inverse threshold and the gray-scale slope share 81% of their variance over six log units of target luminance; in log-log coordinates, 92% of their variance is shared. The strength of the connection improves when negative or positive contrasts are considered separately. Scientific literature is cited, empirical evidence is presented, results of theoretical calculations are discussed, and applications are described. For instance, suprathreshold gray-scale appearance is important in medical imaging, video rendering, industrial process displays, public information displays (e.g., at airports), military situation displays, heads-up displays, multispectral and other abstract scientific imaging, artistic lighting design (e.g., equal-appearing steps of gray scale), and color coding of text, image segments, or symbols for rapid reliable visual search.

An adaptive scale Gaussian filter to explain White's illusion from the viewpoint of lightness assimilation for a large range of variation in spatial frequency of the grating and aspect ratio of the targets

The variation between the actual and perceived lightness of a stimulus has strong dependency on its background, a phenomena commonly known as lightness induction in the literature of visual neuroscience and psychology. For instance, a gray patch may perceptually appear to be darker in a background while it looks brighter when the background is reversed. In the literature it is further reported that such variation can take place in two possible ways. In case of stimulus like the Simultaneous Brightness Contrast (SBC), the apparent lightness changes in the direction opposite to that of the background lightness, a phenomenon often referred to as lightness contrast, while in the others like neon colour spreading or checkerboard illusion it occurs opposite to that, and known as lightness assimilation. The White's illusion is a typical one which according to many, does not completely conform to any of these two processes. This paper presents the result of quantification of the perceptual strength of the White's illusion as a function of the width of the background square grating as well as the length of the gray patch. A linear filter model is further proposed to simulate the possible neurophysiological phenomena responsible for this particular visual experience. The model assumes that for the White's illusion, where the edges are strong and quite a few, i.e., the spectrum is rich in high frequency components, the inhibitory surround in the classical Difference-of-Gaussians (DoG) filter gets suppressed, and the filter essentially reduces to an adaptive scale Gaussian kernel that brings about lightness assimilation. The linear filter model with a Gaussian kernel is used to simulate the White's illusion phenomena with wide variation of spatial frequency of the background grating as well as the length of the gray patch. The appropriateness of the model is presented through simulation results, which are highly tuned to the present as well as earlier psychometric results.

The effect of luminance differences on color assimilation

The color appearance of a surface depends on the color of its surroundings (inducers). When the perceived color shifts towards that of the surroundings, the effect is called "color assimilation" and when it shifts away from the surroundings it is called "color contrast." There is also evidence that the phenomenon depends on the spatial configuration of the inducer, e.g., uniform surrounds tend to induce color contrast and striped surrounds tend to induce color assimilation. However, previous work found that striped surrounds under certain conditions do not induce color assimilation but induce color contrast (or do not induce anything at all), suggesting that luminance differences and high spatial frequencies could be key factors in color assimilation. Here we present a new psychophysical study of color assimilation where we assessed the contribution of luminance differences (between the target and its surround) present in striped stimuli. Our results show that luminance differences are key factors in color assimilation for stimuli varying along the s axis of MacLeod-Boynton color space, but not for stimuli varying along the l axis. This asymmetry suggests that koniocellular neural mechanisms responsible for color assimilation only contribute when there is a luminance difference, supporting the idea that mutual-inhibition has a major role in color induction.

Parallel Processing of Rod and Cone Signals: Retinal Function and Human Perception

We know a good deal about the operation of the retina when either rod or cone photoreceptors provide the dominant input (i.e., under very dim or very bright conditions). However, we know much less about how the retina operates when rods and cones are coactive (i.e., under intermediate lighting conditions, such as dusk). Such mesopic conditions span 20-30% of the light levels over which vision operates and encompass many situations in which vision is essential (e.g., driving at night). These lighting conditions are challenging because rod and cone signals differ substantially: Rod responses are nearing saturation, while cone responses are weak and noisy. A rich history of perceptual studies guides our investigation of how the retina operates under mesopic conditions and in doing so provides a powerful opportunity to link general issues about parallel processing in neural circuits with computation and perception. We review some of the successes and challenges in understanding the retinal basis of perceptual rod-cone interactions.

Sensual Light? Subjective Dimensions of Ambient Illumination

This work concerns the subjective impression of perceived illumination. The purpose of the study is to test attributes expressing qualitative experiences referring to ambient lighting that can be applied as descriptors. Seventy participants viewed an actual model room, with the fourth wall removed (viewing booth). Walls, floor, and ceiling were achromatic. Two achromatic cubes were placed inside the room: One was a reflectance increment to the walls, the other a decrement. The room was illuminated by two different light sources, Artificial Daylight (D65) or Tungsten Filament (F), the order of which was randomized across participants. The participants' task was to evaluate ambient illumination for each light source. A semantic differential method was employed with 27 pairs of adjectives on 1 to 7 rating scales, categorized in three groups: characteristics of atmosphere, time, and cross-modal. Only the ratings of nine pairs of adjectives were not influenced by the type of illumination. The most differentiated couples under different illuminants were hot/cold and modern/old, but large differences also appeared with the following couples: hard/soft, technological/primitive, summery/wintry, warm/cool, sensual/frigid, natural/artificial, and hospitable/inhospitable. The hypothesis that there would be consistency among the subjects in evaluations of the characteristics tested and that these would be differently perceived under different illuminants was confirmed. The results show that it is possible to identify subjective perceived illumination as a phenomenon endowed with specific filling-in qualities and that as a perceptual experience it can be categorized, with implications for application in architecture and design.

The Influence of Physical Illumination on Lightness Perception in Simultaneous Contrast Displays

Three experiments investigated the role of physical illumination on lightness perception in simultaneous lightness contrast (SLC). Four configurations were employed: the classic textbook version of the illusion and three configurations that produced either enhanced or reduced SLC. Experiment 1 tested the effect of ambient illumination on lightness perception. It simulated very dark environmental conditions that nevertheless still allowed perception of different shades of gray. Experiment 2 tested the effect of the intensity of Gelb lighting on lightness perception. Experiment 3 presented two conditions that integrated illumination conditions from Experiments 1 and 2. Our results demonstrated an illumination effect on both lightness matching and perceived SLC contrast: As the intensity of illumination increased, the target on the black background appeared lighter, while the target on the white background was little affected. We hypothesize the existence of two illumination ranges that affect lightness perception differently: low and normal. In the low range, the SLC contrast was reduced and targets appeared darker. In the normal range, the SLC contrast and lightness matchings for each background were little changed across illumination intensities.

A parsimonious model of brightness induction

We present a parsimonious model of brightness induction which can account for various brightness illusions of both brightness-contrast and brightness-assimilation types. Our model is based on a difference of difference-of-Gaussian filter and a two-pass model of attentive vision based on the parallel channels in the central visual pathway. It overcomes some of the problems that could not be addressed by the well-known oriented difference of Gaussian model like those associated with Mach band and checkerboard illusions. This model attempts to provide insight to the mechanism of attention in brightness perception through the two major complimentary visual channels, viz. the magnocellular and the parvocellular.

Packaging of InGaN stripe-shaped light-emitting diodes

We demonstrate the fabrication of InGaN/GaN stripe-shaped light-emitting diodes (LEDs) in flip-chip packaging (FC-LED) and vertically mounted packaging (VM-LED). Compared to conventionally packaged LEDs, these packaging schemes enhance light output and emission divergence in ways favorable for general lighting applications. The FC-LED can sustain efficiency at high current operations due to effective heat sinking, while the VM-LED excels at light extraction efficiency due to the exposure of two large emission surfaces. Together with the properties of low luminous exitance and emission uniformity, the stripe-shaped LEDs are ideal for the assembly of luminaires. An LED light tube comprising a continuous linear array of 10 stripe-shaped LED chips has been assembled. The optical performance of the light tube is compared to another light tube assembled with conventional square-shaped LED chips (with and without external diffuser) by confocal microscopy. It is found that emission uniformity of the stripe-shaped LED tube is significantly improved, with a threefold increase in illumination area, without efficiency loss associated with diffusers.

Transparent effect on the gray scale perception of a transparent OLED display

Gray scale perception of transparent OLED displays was explored. The difference in luminance between transparent and non-transparent stimuli in the overall gray range was compared. The transparent effect appeared in gray scale perception. The range of the transparent effect was determined experimentally. To explore the practical application of this effect, we proposed a new tone-curve based on the transparent effect. In the preference experiment, participants indicated a higher preference score for the new tone-curve. This implied that the transparent effect is valid and applicable to real situations.

The Good, the Bad, and the Ugly: A Theoretical Framework for the Assessment of Continuous Colormaps

A myriad of design rules for what constitutes a "good" colormap can be found in the literature. Some common rules include order, uniformity, and high discriminative power. However, the meaning of many of these terms is often ambiguous or open to interpretation. At times, different authors may use the same term to describe different concepts or the same rule is described by varying nomenclature. These ambiguities stand in the way of collaborative work, the design of experiments to assess the characteristics of colormaps, and automated colormap generation. In this paper, we review current and historical guidelines for colormap design. We propose a specified taxonomy and provide unambiguous mathematical definitions for the most common design rules.

The Effect of Visual Contrast on Human Vestibulo-Ocular Reflex Adaptation

The vestibulo-ocular reflex (VOR) is the main retinal image stabilising mechanism during rapid head movement. When the VOR does not stabilise the world or target image on the retina, retinal image slip occurs generating an error signal that drives the VOR response to increase or decrease until image slip is minimised, i.e. VOR adaptation occurs. Visual target contrast affects the human smooth pursuit and optokinetic reflex responses. We sought to determine if contrast also affected VOR adaptation. We tested 12 normal subjects, each over 16 separate sessions. For sessions 1-14, the ambient light level (lx) during adaptation training was as follows: dark, 0.1, 0.2, 0.3, 0.5, 0.7, 1, 2, 8, 16, 32, 64, 128 and 255 lx (light level for a typical room). For sessions 15-16, the laser target power (related to brightness) was halved with ambient light at 0 and 0.1 lx. The adaptation training lasted 15 min and consisted of left/right active head impulses. The VOR gain was challenged to increment, starting at unity, by 0.1 every 90 s for rotations to the designated adapting side and fixed at unity towards the non-adapting side. We measured active and passive VOR gains before and after adaptation training. We found that for both the active and passive VOR, there was a significant increase in gain only towards the adapting side due to training at contrast level 1.5 k and above (2 lx and below). At contrast level 261 and below (16 lx and above), adaptation training resulted in no difference between adapting and non-adapting side gains. Our modelling suggests that a contrast threshold of ~ 1000, which is 60 times higher than that provided by typical room lighting, must be surpassed for robust active and passive VOR adaptation. Our findings suggest contrast is an important factor for adaptation, which has implication for rehabilitation programs.

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'.

Infants' perception of lightness changes related to cast shadows

When humans perceive the lightness of an object’s surface in shadows there is an implicit assumption that cast shadows dim the surface. In two experiments, we investigated whether 5- to 8-month-old infants make this assumption about shadows. According to this shadow assumption, the apparent change in lightness produced by shadows on an object’s surface are attributed to blocked light sources. If infants can use the shadow assumption to perceive the object’s lightness in shadows, they will also be able to detect unnatural lightness changes in shadows. We compared the infants’ looking times to the unnatural and the natural lightness changes in the shadow when an object (duck) goes through the cast shadow. In Experiment 1, we examined whether infants could detect the unnatural lightness changes of the object’s surface in shadows. We created computer-graphic movies of unnatural and natural lightness changes to the duck’s surface. Our results showed that 7- to 8-month-olds but not 5- to 6-month-olds significantly preferred the movie with the unnatural changes in lightness, indicating that only the older infants could detect these changes. In Experiment 2, we confirmed that the infants’ preference was based on the detection of unnatural lightness changes according to the shadow assumption. The natural and the unnatural lightness changes of Experiment 1 were presented without cast shadows. Under these conditions, neither younger nor older infants showed a significant preference. Taken together, the experiments showed that 7- to 8-month-old infants could detect the unnaturalness of a surface’s lightness changes produced by shadows. In conclusion, our findings suggest that 7- to 8-month-old infants can perceive an object’s lightness in shadows by using an assumption that cast shadows dim the surface of an object.

Separate and Simultaneous Adjustment of Light Qualities in a Real Scene

Humans are able to estimate light field properties in a scene in that they have expectations of the objects’ appearance inside it. Previously, we probed such expectations in a real scene by asking whether a “probe object” fitted a real scene with regard to its lighting. But how well are observers able to interactively adjust the light properties on a “probe object” to its surrounding real scene? Image ambiguities can result in perceptual interactions between light properties. Such interactions formed a major problem for the “readability” of the illumination direction and diffuseness on a matte smooth spherical probe. We found that light direction and diffuseness judgments using a rough sphere as probe were slightly more accurate than when using a smooth sphere, due to the three-dimensional (3D) texture. We here extended the previous work by testing independent and simultaneous (i.e., the light field properties separated one by one or blended together) adjustments of light intensity, direction, and diffuseness using a rough probe. Independently inferred light intensities were close to the veridical values, and the simultaneously inferred light intensity interacted somewhat with the light direction and diffuseness. The independently inferred light directions showed no statistical difference with the simultaneously inferred directions. The light diffuseness inferences correlated with but contracted around medium veridical values. In summary, observers were able to adjust the basic light properties through both independent and simultaneous adjustments. The light intensity, direction, and diffuseness are well “readable” from our rough probe. Our method allows “tuning the light” (adjustment of its spatial distribution) in interfaces for lighting design or perception research.

A Glossy Simultaneous Contrast: Conjoint Measurements of Gloss and Lightness

Interactions between the albedo and the gloss on a surface are commonplace. Darker surfaces are perceived glossier (contrast gloss) than lighter surfaces and darker backgrounds can enhance perceived lightness of surfaces. We used maximum likelihood conjoint measurements to simultaneously quantify the strength of those effects. We quantified the extent to which albedo can influence perceived gloss and physical gloss can influence perceived lightness. We modeled the contribution of lightness and gloss and found that increasing lightness reduced perceived gloss by about 32% whereas gloss had a much weaker influence on perceived lightness of about 12%. Moreover, we also investigated how different backgrounds contribute to the perception of lightness and gloss of a surface placed in front. We found that a glossy background reduces slightly perceived lightness of the center and simultaneously enhances its perceived gloss. Lighter backgrounds reduce perceived gloss and perceived lightness. Conjoint measurements lead us to a better understanding of the contextual effects in gloss and lightness perception. Not only do we confirm the importance of contrast in gloss perception and the reduction of the simultaneous contrast with glossy backgrounds, but we also quantify precisely the strength of those effects.

Retinal Lateral Inhibition Provides the Biological Basis of Long-Range Spatial Induction

Retinal lateral inhibition is one of the conventional efficient coding mechanisms in the visual system that is produced by interneurons that pool signals over a neighborhood of presynaptic feedforward cells and send inhibitory signals back to them. Thus, the receptive-field (RF) of a retinal ganglion cell has a center-surround receptive-field (RF) profile that is classically represented as a difference-of-Gaussian (DOG) adequate for efficient spatial contrast coding. The DOG RF profile has been attributed to produce the psychophysical phenomena of brightness induction, in which the perceived brightness of an object is affected by that of its vicinity, either shifting away from it (brightness contrast) or becoming more similar to it (brightness assimilation) depending on the size of the surfaces surrounding the object. While brightness contrast can be modeled using a DOG with a narrow surround, brightness assimilation requires a wide suppressive surround. Early retinal studies determined that the suppressive surround of a retinal ganglion cell is narrow (< 100–300 μm; ‘classic RF’), which led researchers to postulate that brightness assimilation must originate at some post-retinal, possibly cortical, stage where long-range interactions are feasible. However, more recent studies have reported that the retinal interneurons also exhibit a spatially wide component (> 500–1000 μm). In the current study, we examine the effect of this wide interneuron RF component in two biophysical retinal models and show that for both of the retinal models it explains the long-range effect evidenced in simultaneous brightness induction phenomena and that the spatial extent of this long-range effect of the retinal model responses matches that of perceptual data. These results suggest that the retinal lateral inhibition mechanism alone can regulate local as well as long-range spatial induction through the narrow and wide RF components of retinal interneurons, arguing against the existing view that spatial induction is operated by two separate local vs. long-range mechanisms.