Nearly instantaneous brightness induction

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.

Color appearance shift in augmented reality metameric matching

The physical additivity of optical-see-through (OST) augmented reality (AR), where display and the real-world overlay with each other, impacts its color appearance. We explored this unique dynamic by looking at the effect of background correlated color temperature (CCT) on AR color appearance with a color matching experiment between a prototype OST-AR RGB system and daylight spectrum reproduction. Different background CCT, luminance levels, and two stimulus types [simulated two-dimensional (2D) disk and three-dimensional (3D) cube] were examined. We found that when the background color is inconsistent with the stimulus providing conflicted cues, matched colors in AR shifted towards the background. The luminance matched on the 3D cube is higher than the 2D disk, suggesting the impact of context on the AR appearance. A controlled metameric matching group between daylight reproduction and LCD or CRT did not show the shift, indicating that the appearance shift is not due to the RGB-spectrum metameric matching, but due to RGB foreground-spectral background interaction beyond simple additivity. How perceptual weighting on the foreground and background is modified to predict the appearance as a function of additivity is discussed.

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.

Lightness induction enhancements and limitations at low frequency modulations across a variety of stimulus contexts

Lightness illusions are often studied under static viewing conditions with figures varying in geometric design, containing different types of perceptual grouping and figure-ground cues. A few studies have explored the perception of lightness induction while modulating lightness illusions continuously in time, where changes in perceived lightness are often linked to the temporal modulation frequency, up to around 2–4 Hz. These findings support the concept of a cut-off frequency for lightness induction. However, another critical change (enhancement) in the magnitude of perceived lightness during slower temporal modulation conditions has not been addressed in previous temporal modulation studies. Moreover, it remains unclear whether this critical change applies to a variety of lightness illusion stimuli, and the degree to which different stimulus configurations can demonstrate enhanced lightness induction in low modulation frequencies. Therefore, we measured lightness induction strength by having participants cancel out any perceived modulation in lightness detected over time within a central target region, while the surrounding context, which ultimately drives the lightness illusion, was viewed in a static state or modulated continuously in time over a low frequency range (0.25–2 Hz). In general, lightness induction decreased as temporal modulation frequency was increased, with the strongest perceived lightness induction occurring at lower modulation frequencies for visual illusions with strong grouping and figure-ground cues. When compared to static viewing conditions, we found that slow continuous surround modulation induces a strong and significant increase in perceived lightness for multiple types of lightness induction stimuli. Stimuli with perceptually ambiguous grouping and figure-ground cues showed weaker effects of slow modulation lightness enhancement. Our results demonstrate that, in addition to the existence of a cut-off frequency, an additional critical temporal modulation frequency of lightness induction exists (0.25–0.5 Hz), which instead maximally enhances lightness induction and seems to be contingent upon the prevalence of figure-ground and grouping organization.

A power law study of the edge influence on the perceived filling-in brightness magnitude

Abstract

Background

Edge plays a special role in spatial perception and as well as in determining the brightness of a surface within borders. The aim of our study was to measure threshold brightness in different levels of edges thickness.

Methods

Steven’s power law for circles modulating in luminance was estimated for 30 subjects (mean age 24 years, SD 3.3, 13 female). Stimuli were presented on the iMac display using the 11-bit graphic board and consisted of two circles of 3° of visual angle, separated by 10°. We tested 7 levels of Michelson contrast: 7, 8, 10, 15, 26, 50, and 100. Three edges filtering were tested (0.3, 0.8, and 1.5° of smoothing). The subjects’ task was to judge the brightness of the edge filtered circle compared with the circle of the hard edge which was considered the modulus and received an arbitrary level of 50, representing the amount of brightness perception. In each trial, the same contrast level was presented in both circles. Five judgments were performed for each contrast level in edge filtering.

Results

We found an increase in the power law exponent as the increase of the edge filtering (for sigma of 0.3 = 0.43, sigma of 0.8 = 0.73, and sigma 1.5 = 0.97). All power function fitting had high correlation coefficients (r² = .94, r² = .95, r² = .97, respectively to sigma 0.3, 0.8, and 1.5) passing to the model’s adhesion criteria.

Conclusions

There was a progressive distortion on the figure brightness perception as increasing the edge filtering suggesting the control of edges on the polarity of the overall brightness. Also, perceived brightness was increasingly veridical with increased filtering, approaching 1:1 correspondence at 1.5 sigmas.

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.

Individual Variability in Simultaneous Contrast for Color and Brightness: Small Sample Factor Analyses Reveal Separate Induction Processes for Short and Long Flashes

In classic simultaneous color contrast and simultaneous brightness contrast, the color or brightness of a stimulus appears to shift toward the complementary (opposite) color or brightness of its surrounding region. Kaneko and colleagues proposed that simultaneous contrast involves separate "fast" and "slow" mechanisms, with stronger induction effects for fast than slow. Support for the model came from a diverse series of experiments showing that induction by surrounds varying in luminance or color was stronger for brief than long presentation times (10-40 vs. 80-640 ms). Here, to further examine possible underlying processes, we reanalyzed 12 separate small data sets from these studies using correlational and factor analytic techniques. For each analysis, a principal component analysis of induction strength revealed two factors, with one Varimax-rotated factor accounting for brief and one for long durations. In simultaneous brightness experiments, separate factor pairs were obtained for luminance increments and decrements. Despite being based on small sample sizes, the two-factor consistency among 12 analyses would not be expected by chance. The results are consistent with separate fast and slow processes mediating simultaneous contrast for brief and long flashes.

Stereoscopic Slant Contrast and the Perception of Inducer Slant at Brief Stimulus Presentations

Slant contrast refers to a stereoscopic phenomenon in which the perceived slant of a test object is affected by the disparity of a surrounding inducer object. Slant contrast has been proposed to involve cue conflict, but it is unclear whether this idea is useful in explaining slant contrast at short stimulus presentations (<1 s). We measured both slant contrast and perceived inducer slant while varying the presentation duration (100-800 ms) of stereograms with several spatial configurations. In three psychophysical experiments, we found that (a) both slant contrast and perceived inducer slant increased as a function of stimulus duration, and (b) slant contrast was relatively stable across different test and inducer shapes at each short stimulus duration, whereas perceived inducer slant increased when cue conflict was reduced. These results suggest that at brief, not long stimulus presentations, the cue conflict between disparity and perspective plays a smaller role in slant contrast than other depth cues.

Visual evoked potentials to an illusory change in brightness: the Craik-Cornsweet-O'Brien effect

Can brain electrical activity associated with the Craik-Cornsweet-O'Brien effect (CCOB) be identified in humans? Opposing luminance gradients met in the middle of a square image to create a luminance contrast-defined vertical border. The resulting rectangles on each side of the border were otherwise equiluminant, but appeared to differ in brightness, the CCOB effect. When the contrast gradients were swapped, the participants perceived darker and lighter rectangles trading places. This dynamic CCOB stimulus was reversed 1/s to elicit visual evoked potentials. The CCOB effect was absent in two control conditions. In one, the immediate contrast border, where the gradients met, was replaced by a dark vertical stripe; in the other, the outer segments of both rectangles, where the illusion would otherwise occur, were replaced by dark rectangles, leaving only the contrast-reversing gradients. Visual evoked potential components P1 and N2 were present for the CCOB stimuli, but not the control stimuli. Results are consistent with functional MRI and single unit evidence, suggesting that the brightness of the CCOB effect becomes dissociated from the luminance falling on the eye early in visual processing. These results favor explanations of brightness induction invoking rapid, early amplification of very low spatial-frequency information in the image to approximate natural scenes as opposed to a sluggish brightness adjustment spreading from the contrast border.

Influence of surround proximity on induction of brown and darkness

A bright white surround makes a yellow long-wavelength target look both browner and darker. We explored the parallel between these two types of induction by examining their dependence on the proximity of the bright surround to the target at two different time scales with 27 ms and 1 s stimulus durations. We assessed (a) brown induction by adjustment of target luminance to perceptual brown and yellow boundaries and (b) darkness induction by a successive matching procedure. We found that brown induction is a quick process that is robust even for 27 ms stimuli. For darkness induction, there was a strong, spatially localized surround proximity effect for the 27 ms stimuli and much weaker proximity effect for the 1 s stimuli. For brown induction, proximity effects were generally weaker but still showed relatively stronger localized proximity effects for 27 ms stimuli than for 1 s stimuli. For these stimuli, darkness induction predicts the relative pattern but not the magnitudes of brown induction. Both brown and darkness inductions show the operation of quick, spatially localized processes that are apparently superseded by other processes for extended stimulus presentations.

Testing the role of luminance edges in White's illusion with contour adaptation

White's illusion is the perceptual effect that two equiluminant gray patches superimposed on a black-and-white square-wave grating appear different in lightness: A test patch placed on a dark stripe of the grating looks lighter than one placed on a light stripe. Although the effect does not depend on the aspect ratio of the test patches, and thus on the amount of border that is shared with either the dark or the light stripe, the context of each patch must, in a yet to be specified way, influence their lightness. We employed a contour adaptation paradigm (Anstis, 2013) to test the contribution of each of the test patches' edges to the perceived lightness of the test patches. We found that adapting to the edges that are oriented parallel to the grating slightly increased the lightness illusion, whereas adapting to the orthogonal edges abolished, or for some observers even reversed, the lightness illusion. We implemented a temporal adaptation mechanism in three spatial filtering models of lightness perception, and show that the models cannot account for the observed adaptation effects. We conclude that White's illusion is largely determined by edge contrast across the edge orthogonal to the grating, whereas the parallel edge has little or no influence. We suggest mechanisms that could explain this asymmetry.

Contour Erasure and Filling-in: Old Simulations Account for Most New Observations

Three recent studies used similar stimulus sequences to investigate mechanisms for brightness perception. Anstis and Greenlee (2014) demonstrated that adaptation to a flickering black and white outline erased the visibility of a subsequent target shape defined by a luminance increment or decrement. Robinson and de Sa (2012, 2013) used a flickering disk or annulus to show a similar effect. Here, a neural network model of visual perception (Francis & Kim, 2012), that previously explained properties of scene fading, is shown to also explain most of the erasure effects reported by Anstis and Greenlee and by Robinson and de Sa. The model proposes that in normal viewing conditions a brightness filling-in process is constrained by oriented boundaries, which thereby define separate regions of a visual scene. Contour adaptation can weaken the boundaries and thereby allow brightness signals to merge together, which renders target stimuli indistinguishable from the background. New simulations with the stimuli used by Anstis and Greenlee and Robinson and de Sa produce model output very similar to the perceptual experience of human observers. Finally, the model predicts that adaptation to illusory contours will not produce contour erasure.

Brightness induction and suprathreshold vision: effects of age and visual field

A variety of visual capacities show significant age-related alterations. We assessed suprathreshold contrast and brightness perception across the lifespan in a large sample of healthy participants (N=155; 142) ranging in age from 16 to 80 years. Experiment 1 used a quadrature-phase motion cancelation technique (Blakeslee & McCourt, 2008) to measure canceling contrast (in central vision) for induced gratings at two temporal frequencies (1 Hz and 4 Hz) at two test field heights (0.5° or 2°×38.7°; 0.052 c/d). There was a significant age-related reduction in canceling contrast at 4 Hz, but not at 1 Hz. We find no age-related change in induction magnitude in the 1 Hz condition. We interpret the age-related decline in grating induction magnitude at 4 Hz to reflect a diminished capacity for inhibitory processing at higher temporal frequencies. In Experiment 2 participants adjusted the contrast of a matching grating (0.5° or 2°×38.7°; 0.052 c/d) to equal that of both real (30% contrast, 0.052 c/d) and induced (McCourt, 1982) standard gratings (100% inducing grating contrast; 0.052 c/d). Matching gratings appeared in the upper visual field (UVF) and test gratings appeared in the lower visual field (LVF), and vice versa, at eccentricities of ±7.5°. Average induction magnitude was invariant with age for both test field heights. There was a significant age-related reduction in perceived contrast of stimuli in the LVF versus UVF for both real and induced gratings.

A temporal window for estimating surface brightness in the Craik-O'Brien-Cornsweet effect

The central edge of an opposing pair of luminance gradients (COC edge) makes adjoining regions with identical luminance appear to be different. This brightness illusion, called the Craik-O'Brien-Cornsweet effect (COCe), can be explained by low-level spatial filtering mechanisms (Dakin and Bex, 2003). Also, the COCe is greatly reduced when the stimulus lacks a frame element surrounding the COC edge (Purves et al., 1999). This indicates that the COCe can be modulated by extra contextual cues that are related to ideas about lighting priors. In this study, we examined whether processing for contextual modulation could be independent of the main COCe processing mediated by the filtering mechanism. We displayed the COC edge and frame element at physically different times. Then, while varying the onset asynchrony between them and changing the luminance contrast of the frame element, we measured the size of the COCe. We found that the COCe was observed in the temporal range of around 600–800 ms centered at the 0 ms (from around −400 to 400 ms in stimulus onset asynchrony), which was much larger than the range of typical visual persistency. More importantly, this temporal range did not change significantly regardless of differences in the luminance contrast of the frame element (5–100%), in the durations of COC edge and/or the frame element (50 or 200 ms), in the display condition (interocular or binocular), and in the type of lines constituting the frame element (solid or illusory lines). Results suggest that the visual system can bind the COC edge and frame element with a temporal window of ~1 s to estimate surface brightness. Information from the basic filtering mechanism and information of contextual cue are separately processed and are linked afterwards.

Orientation enhancement in early visual processing can explain time course of brightness contrast and White's illusion

Dynamics of orientation tuning in V1 indicates that computational model of V1 should not only comprise of bank of static spatially oriented filters but also include the contribution for dynamical response facilitation or suppression along orientation. Time evolution of orientation response in V1 can emerge due to time- dependent excitation and lateral inhibition in the orientation domain. Lateral inhibition in the orientation domain suggests that Ernst Mach's proposition can be applied for the enhancement of initial orientation distribution that is generated due to interaction of visual stimulus with spatially oriented filters and subcortical temporal filter. Oriented spatial filtering that appears much early (<70 ms) in the sequence of visual information processing can account for many of the brightness illusions observed at steady state. It is therefore expected that time evolution of orientation response might be reflecting in the brightness percept over time. Our numerical study suggests that only spatio-temporal filtering at early phase can explain experimentally observed temporal dynamics of brightness contrast illusion. But, enhancement of orientation response at early phase of visual processing is the key mechanism that can guide visual system to predict the brightness by "Max-rule" or "Winner Takes All" (WTA) estimation and thus producing White's illusions at any exposure.

Brightness induction magnitude declines with increasing distance from the inducing field edge

Brightness induction refers to a class of visual illusions where the perceived intensity of a region of space is influenced by the luminance of surrounding regions. These illusions are significant because they provide insight into the neural organization and processing strategies employed by the visual system. The nature of these processing strategies, however, has long been debated. Here we investigate the spatial characteristics of grating induction as a function of the distance from the inducing field edge to evaluate the viability of various competing models. In particular multiscale spatial filtering models and homogeneous filling-in models make very different predictions in regard to the magnitude of induction as a function of this distance. Filling-in explanations predict that the brightness/lightness of the filled-in region will be homogeneous, whereas multiscale filtering predicts a fall-off in induction magnitude with distance from the inducing field edge. Induction magnitude was measured using a narrow probe version of the quadrature-phase motion-cancellation paradigm (Blakeslee & McCourt, 2011) and a point-by-point brightness matching paradigm (Blakeslee & McCourt, 1997, 1999; McCourt, 1994). Both techniques reveal a decrease in the magnitude of induction with increasing distance from the inducing edge. A homogeneous filling-in mechanism cannot explain the induced structure in the test fields of these stimuli. The results argue strongly against filling-in mechanisms as well as against any mechanism that posits that induction is homogeneous. The structure of the induction is, however, well accounted for by the multiscale filtering (ODOG) model of Blakeslee and McCourt (1999). These results support models of brightness/lightness, such as filtering models, which preserve these gradients of induction.

Spatiotemporal analysis of brightness induction

Brightness induction refers to a class of visual illusions in which the perceived intensity of a region of space is influenced by the luminance of surrounding regions. These illusions are significant because they provide insight into the neural organization of the visual system. A novel quadrature-phase motion cancelation technique was developed to measure the magnitude of the grating induction brightness illusion across a wide range of spatial frequencies, temporal frequencies and test field heights. Canceling contrast is greatest at low frequencies and declines with increasing frequency in both dimensions, and with increasing test field height. Canceling contrast scales as the product of inducing grating spatial frequency and test field height (the number of inducing grating cycles per test field height). When plotted using a spatial axis which indexes this product, the spatiotemporal induction surfaces for four test field heights can be described as four partially overlapping sections of a single larger surface. These properties of brightness induction are explained in the context of multiscale spatial filtering. The present study is the first to measure the magnitude of grating induction as a function of temporal frequency. Taken in conjunction with several other studies (Blakeslee & McCourt, 2008; Magnussen & Glad, 1975; Robinson & de Sa, 2008) the results of this study illustrate that at least one form of brightness induction is very much faster than that reported by DeValois, Webster, DeValois, and Lingelbach (1986) and Rossi and Paradiso (1996), and are inconsistent with the proposition that brightness induction results from a slow "filling in" process.

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.

Induced temporal variation at frequencies not in the stimulus: evidence for a neural nonlinearity

The perceived color of a light depends on surrounding light. When the surround varies slowly over time, a central, physically steady light is perceived to vary also. This perceived temporal variation of the central region, however, is strongly attenuated when the surround varies faster than approximately 3 Hz (R. L. De Valois, M. A. Webster, K. K. De Valois, & B. Lingelbach, 1986). The classical explanation is low-pass temporal filtering at a cortical stage that attenuates the neural representation of temporal frequencies capable of causing induced temporal variation. This theory assumes neural responses are linear, so only temporal frequencies in the stimulus are represented in the neural response. The current experiments revealed that temporal frequencies above 3 Hz are capable of inducing temporal variation. Specifically, with two temporal frequencies superimposed in the surround, the induced temporal variation in the uniform region is at the difference frequency of these two frequencies, even though this frequency is not physically present in the stimulus. The results are accounted for by a nonlinear neural process, which causes temporal variation at the difference frequency, and a following linear temporal filter.

Spatial and temporal influences on the contrast gauge

A contrast gauge consists of a narrow bar shaded from dark on bottom to light on top [Shapiro, A. G., Charles, J. P., & Shear-Heyman, M. (2005). Visual illusions based on single-field contrast asynchronies. Journal of Vision, 5(10), 764-782]. The perceptual division between dark and light on the bar depends on the luminance level of the surround: when the surround has a high luminance level, the perceptual divider moves up the bar; when the surround has a low luminance level, the perceptual divider moves down the bar. This paper examines the extent to which the perceptual division between light and dark can be used as an indicator to mark the zero contrast level between the bar and the surround. In the experiments, the bar was surrounded by a field whose luminance modulated in time. Three observers marked the maximum and minimum levels of the perceptual divider as a function of modulation amplitude, chromaticity (R, G, B, W), temporal frequency, and width of the surround. Linear changes in the modulation amplitude of the surround produced linear changes in the observers' settings of the indicator. Observer settings matched zero luminance contrast when the surround was wide (12.5deg), was modulating at less than or equal to 1Hz, and had W or G chromaticity, but not when the surround was narrow, or was modulating faster than 1Hz, or had R or B chromaticity. The effects of surround size suggest that the perceived minimum contrast results from processes that operate over multiple spatial scales. To test this hypothesis, the paper presents a new configuration in which near and far contrast information create different perceptual signatures. Under normal viewing conditions, the motion of the indicator follows the contrast information from the nearest edge, but when high spatial frequency information is removed (through image blur), the motion follows the contrast from the far spatial edge. It is therefore likely that the setting for the indicator for the contrast gauge depends on multiple processes and is not a simple indicator of luminance contrast. The perceptual response to low spatial frequency contrast appears to be given less perceptual weight when high spatial frequencies are present in the image.