Motion sharpening and contrast:Gain control precedes compressive non-linearity?

Blurred edges appear sharper in motion than when they are stationary. We (Vision Research 38 (1998) 2108) have previously shown how such distortions in perceived edge blur may be accounted for by a model which assumes that luminance contrast is encoded by a local contrast transducer whose response becomes progressively more compressive as speed increases. If the form of the transducer is fixed (independent of contrast) for a given speed, then a strong prediction of the model is that motion sharpening should increase with increasing contrast. We measured the sharpening of periodic patterns over a large range of contrasts, blur widths and speeds. The results indicate that whilst sharpening increases with speed it is practically invariant with contrast. The contrast invariance of motion sharpening is not explained by an early, static compressive non-linearity alone. However, several alternative explanations are also inconsistent with these results. We show that if a dynamic contrast gain control precedes the static non-linear transducer then motion sharpening, its speed dependence, and its invariance with contrast, can be predicted with reasonable accuracy. © 2003 Elsevier Science Ltd. All rights reserved.

A model for motion sharpening: contrast gain control precedes compressive nonlinearity

Blurred edges appear sharper in motion than when they are stationary. We have previously shown how such distortions in perceived edge blur may be explained by a model which assumes that luminance contrast is encoded by a local contrast transducer whose response becomes progressively more compressive as speed increases. To test this model further, we measured the sharpening of drifting, periodic patterns over a large range of contrasts, blur widths, and speeds Human Vision. The results indicate that, while sharpening increased with speed, it was practically invariant with contrast. This contrast invariance cannot be explained by a fixed compressive nonlinearity since that predicts almost no sharpening at low contrasts.We show by computational modelling of spatiotemporal responses that, if a dynamic contrast gain control precedes the static nonlinear transducer, then motion sharpening, its speed dependence, and its invariance with contrast can be predicted with reasonable accuracy.

Perceiving edge blur: linear filtering and a rectifying nonlinearity

We studied the visual mechanisms that encode edge blur in images. Our previous work suggested that the visual system spatially differentiates the luminance profile twice to create the 'signature' of the edge, and then evaluates the spatial scale of this signature profile by applying Gaussian derivative templates of different sizes. The scale of the best-fitting template indicates the blur of the edge. In blur-matching experiments, a staircase procedure was used to adjust the blur of a comparison edge (40% contrast, 0.3 s duration) until it appeared to match the blur of test edges at different contrasts (5% - 40%) and blurs (6 - 32 min of arc). Results showed that lower-contrast edges looked progressively sharper.We also added a linear luminance gradient to blurred test edges. When the added gradient was of opposite polarity to the edge gradient, it made the edge look progressively sharper. Both effects can be explained quantitatively by the action of a half-wave rectifying nonlinearity that sits between the first and second (linear) differentiating stages. This rectifier was introduced to account for a range of other effects on perceived blur (Barbieri-Hesse and Georgeson, 2002 Perception 31 Supplement, 54), but it readily predicts the influence of the negative ramp. The effect of contrast arises because the rectifier has a threshold: it not only suppresses negative values but also small positive values. At low contrasts, more of the gradient profile falls below threshold and its effective spatial scale shrinks in size, leading to perceived sharpening.

Shading and texture:Separate information channels with a common adaptation mechanism?

We outline a scheme for the way in which early vision may handle information about shading (luminance modulation, LM) and texture (contrast modulation, CM). Previous work on the detection of gratings has found no sub-threshold summation, and no cross-adaptation, between LM and CM patterns. This strongly implied separate channels for the detection of LM and CM structure. However, we now report experiments in which adapting to LM (or CM) gratings creates tilt aftereffects of similar magnitude on both LM and CM test gratings, and reduces the perceived strength (modulation depth) of LM and CM gratings to a similar extent. This transfer of aftereffects between LM and CM might suggest a second stage of processing at which LM and CM information is integrated. The nature of this integration, however, is unclear and several simple predictions are not fulfilled. Firstly, one might expect the integration stage to lose identity information about whether the pattern was LM or CM. We show instead that the identity of barely detectable LM and CM patterns is not lost. Secondly, when LM and CM gratings are combined in-phase or out-of-phase we find no evidence for cancellation, nor for 'phase-blindness'. These results suggest that information about LM and CM is not pooled or merged - shading is not confused with texture variation. We suggest that LM and CM signals are carried by separate channels, but they share a common adaptation mechanism that accounts for the almost complete transfer of perceptual aftereffects.

Template model for blur coding: the role of early nonlinearity in edge segmentation

We describe a template model for perception of edge blur and identify a crucial early nonlinearity in this process. The main principle is to spatially filter the edge image to produce a 'signature', and then find which of a set of templates best fits that signature. Psychophysical blur-matching data strongly support the use of a second-derivative signature, coupled to Gaussian first-derivative templates. The spatial scale of the best-fitting template signals the edge blur. This model predicts blur-matching data accurately for a wide variety of Gaussian and non-Gaussian edges, but it suffers a bias when edges of opposite sign come close together in sine-wave gratings and other periodic images. This anomaly suggests a second general principle: the region of an image that 'belongs' to a given edge should have a consistent sign or direction of luminance gradient. Segmentation of the gradient profile into regions of common sign is achieved by implementing the second-derivative 'signature' operator as two first-derivative operators separated by a half-wave rectifier. This multiscale system of nonlinear filters predicts perceived blur accurately for periodic and aperiodic waveforms. We also outline its extension to 2-D images and infer the 2-D shape of the receptive fields.

Seeing edge blur: receptive fields as multiscale neural templates

Edge blur is an important perceptual cue, but how does the visual system encode the degree of blur at edges? Blur could be measured by the width of the luminance gradient profile, peak ^ trough separation in the 2nd derivative profile, or the ratio of 1st-to-3rd derivative magnitudes. In template models, the system would store a set of templates of different sizes and find which one best fits the `signature' of the edge. The signature could be the luminance profile itself, or one of its spatial derivatives. I tested these possibilities in blur-matching experiments. In a 2AFC staircase procedure, observers adjusted the blur of Gaussian edges (30% contrast) to match the perceived blur of various non-Gaussian test edges. In experiment 1, test stimuli were mixtures of 2 Gaussian edges (eg 10 and 30 min of arc blur) at the same location, while in experiment 2, test stimuli were formed from a blurred edge sharpened to different extents by a compressive transformation. Predictions of the various models were tested against the blur-matching data, but only one model was strongly supported. This was the template model, in which the input signature is the 2nd derivative of the luminance profile, and the templates are applied to this signature at the zero-crossings. The templates are Gaussian derivative receptive fields that covary in width and length to form a self-similar set (ie same shape, different sizes). This naturally predicts that shorter edges should look sharper. As edge length gets shorter, responses of longer templates drop more than shorter ones, and so the response distribution shifts towards shorter (smaller) templates, signalling a sharper edge. The data confirmed this, including the scale-invariance implied by self-similarity, and a good fit was obtained from templates with a length-to-width ratio of about 1. The simultaneous analysis of edge blur and edge location may offer a new solution to the multiscale problem in edge detection.

Associative knowledge controls deployment of visual selective attention

According to some models of visual selective attention, objects in a scene activate corresponding neural representations, which compete for perceptual awareness and motor behavior. During a visual search for a target object, top-down control exerted by working memory representations of the target's defining properties resolves competition in favor of the target. These models, however, ignore the existence of associative links among object representations. Here we show that such associations can strongly influence deployment of attention in humans. In the context of visual search, objects associated with the target were both recalled more often and recognized more accurately than unrelated distractors. Notably, both target and associated objects competitively weakened recognition of unrelated distractors and slowed responses to a luminance probe. Moreover, in a speeded search protocol, associated objects rendered search both slower and less accurate. Finally, the first saccades after onset of the stimulus array were more often directed toward associated than control items.

Grating and plaid masks indicate linear summation in a contrast gain pool

In human vision, the response to luminance contrast at each small region in the image is controlled by a more global process where suppressive signals are pooled over spatial frequency and orientation bands. But what rules govern summation among stimulus components within the suppressive pool? We addressed this question by extending a pedestal plus pattern mask paradigm to use a stimulus with up to three mask components: a vertical 1 c/deg pedestal, plus pattern masks made from either a grating (orientation = -45°) or a plaid (orientation = ±45°), with component spatial frequency of 3 c/deg. The overall contrast of both types of pattern mask was fixed at 20% (i.e., plaid component contrasts were 10%). We found that both of these masks transformed conventional dipper functions (threshold vs. pedestal contrast with no pattern mask) in exactly the same way: The dipper region was raised and shifted to the right, but the dipper handles superimposed. This equivalence of the two pattern masks indicates that contrast summation between the plaid components was perfectly linear prior to the masking stage. Furthermore, the pattern masks did not drive the detecting mechanism above its detection threshold because they did not abolish facilitation by the pedestal (Foley, 1994). Therefore, the pattern masking could not be attributed to within-channel masking, suggesting that linear summation of contrast signals takes place within a suppressive contrast gain pool. We present a quantitative model of the effects and discuss the implications for neurophysiological models of the process. © 2004 ARVO.

The influence of age on the pattern and flash visual evoked magnetic response (VEMR)

The visual evoked magnetic response (VEMR) was measured over the occipital cortex to pattern and flash stimuli in 86 normal subjects aged 15-86 years. The latency of the major positive component (outgoing magnetic field) to the pattern reversal stimulus (P100M) increased with age, particularly after 55 years, while the amplitude of the P100M decreased more gradually over the lifespan. By contrast, the latency of the major positive component to the flash stimulus (P2M) increased more slowly with age after about 50 years, while its amplitude may have decreased in only a proportion of the elderly subjects. The changes in the P100M with age may reflect senile changes in the eye and optic nerve, e.g. senile miosis, degenerative changes in the retina or geniculostriate deficits. The P2M may be more susceptible to senile changes in the visual cortex. The data suggest that the contrast channels of visual information processing deteriorate more rapidly with age than the luminance channels.

What is second-order vision for? Discriminating illumination versus material changes

The human visual system is sensitive to second-order modulations of the local contrast (CM) or amplitude (AM) of a carrier signal. Second-order cues are detected independently of first-order luminance signals; however, it is not clear why vision should benet from second-order sensitivity. Analysis of the first-and second-order contents of natural images suggests that these cues tend to occur together, but their phase relationship varies. We have shown that in-phase combinations of LM and AM are perceived as a shaded corrugated surface whereas the anti-phase combination can be seen as corrugated when presented alone or as a flat material change when presented in a plaid containing the in-phase cue. We now extend these findings using new stimulus types and a novel haptic matching task. We also introduce a computational model based on initially separate first-and second-order channels that are combined within orientation and subsequently across orientation to produce a shading signal. Contrast gain control allows the LM + AM cue to suppress responses to the LM-AM when presented in a plaid. Thus, the model sees LM -AM as flat in these circumstances. We conclude that second-order vision plays a key role in disambiguating the origin of luminance changes within an image. © ARVO.

Sun and sky:does human vision assume a mixture of point and diffuse illumination when interpreting shape-from-shading?

People readily perceive smooth luminance variations as being due to the shading produced by undulations of a 3-D surface (shape-from-shading). In doing so, the visual system must simultaneously estimate the shape of the surface and the nature of the illumination. Remarkably, shape-from-shading operates even when both these properties are unknown and neither can be estimated directly from the image. In such circumstances humans are thought to adopt a default illumination model. A widely held view is that the default illuminant is a point source located above the observer's head. However, some have argued instead that the default illuminant is a diffuse source. We now present evidence that humans may adopt a flexible illumination model that includes both diffuse and point source elements. Our model estimates a direction for the point source and then weights the contribution of this source according to a bias function. For most people the preferred illuminant direction is overhead with a strong diffuse component.

The influence of age on the pattern and flash visual evoked field

We have investigated the effect of ageing on the visual system using the relatively new technique of magentoencephalography (MEG). This technique measures the magnetic signals produced by the visual system using a SQUID magnetometer. The magnetic visual evoked field (VEF) was measured over the occipital cortex to pattern and flash stimuli in 86 normal subjects aged 15 - 86 years. Factors that influenced subject defocussing or defixating the stimulus or selective attention were controlled as far as possible. The latency of the major positive component to the pattern reversal stimulus (P100M) increased with age particularly after the age of 55 years while the amplitude of the P100M decreased over the life span. The latency of the major flash component (P2M) increased much more slowly with age, while its amplitude decreased in only a proportion of elderly subjects. Changes in the P100M with age may reflect senile changes in the eye and optic nerve, e.g. senile miosis or degenerative changes in the retina. The P2M may be more susceptible to senile changes in the retina. The data suggest that the spatial frequency channels deteriorate more rapidly with age than the luminance channels and that MEG may be an effective method of studying ageing in the visual system.

Topography of visual evoked magnetic responses to pattern shift, pattern onset and flash stimuli

Different visual stimuli may activate separate channels in the visual system and produce magnetic responses from the human bran which originate from distinct regions of the visual cortex. To test this hypothesis, we have investigated the distribution of visual evoked magnetic responses to three distinct visual stimuli over the occipital region of the scalp with a DC-SQUID second-order gradiometer in an ubshielded environment. Patterned stimuli were presented full field and to the right half field, while a flash stimulus was presented full field only, in five normal subjects. Magnetic responses were recorded from 20 to 42 positions over the occipital scalp. Topographic maps were prepared of the major positive component within the first 150ms to the three stimuli, i.e., the P100m (pattern shift), C11m (pattern onset) and P2m (flash). For the pattern shift stimulus the data suggested the source of the P100m was close to the midline with the current directed towards the medial surface. The data for the pattern onset C11m suggested a source at a similar depth but with the current directed away from the midline towards the lateral surface. The flash P2m appeared to originate closer to the surface of the occipital pole than both the patterned stimuli. Hence the pattern shift (which may represent movement), and the pattern onset C11m (representing contrast and contour) appear to originate in similar areas of brain but to represent different asepcts of cortical processing. By contrast, the flash P2m (representing luminance change) appears to originate in a distinct area of visual cortex closer to the occipital pole.

Continuous measurement of accommodation in human factor applications

It has long been sought to measure ocular accommodation continuously in human factor applications such as driving or flying. Open-field autorefractors such as the Canon R-1 could be converted to allow continuous, objective recording, but steady eye fixation and head immobilisation were essential for the measurements to be valid. Image analysis techniques utilised by newer open-view autorefractors such as the Shin-Nippon SRW-5000 are more tolerant to head and eye movements, but perhaps the technique with the greatest potential for the measurement of accommodation in human factor applications is photoretinoscopy. This paper examines the development of techniques for high temporal measurements of accommodation and reports on the tolerance of one such recent commercial instrument, the PowerRefractor (PlusOptiX). The instrument was found to be tolerant to eye movements from the optical axis of the instrument (∼0.50 DS change in apparent accommodation with gaze 25° eccentric to the optical axis), longitudinal head movement (<0.25 DS from 8 cm towards and 20 cm away from the correct photorefractor to eye distance) and changes in background illuminance (<0.25 DS from 0.5 to 20 cd m-2 target luminance). The PowerRefractor also quantifies the direction of gaze and pupil size, but is unable to take measurements with small pupils <3.7 ±1.0 mm. © 2002 The College of Optometrists.

Contrast summation across eyes and space is revealed along the entire dipper function by a "Swiss cheese" stimulus.

Previous contrast discrimination experiments have shown that luminance contrast is summed across ocular (T. S. Meese, M. A. Georgeson, & D. H. Baker, 2006) and spatial (T. S. Meese & R. J. Summers, 2007) dimensions at threshold and above. However, is this process sufficiently general to operate across the conjunction of eyes and space? Here we used a "Swiss cheese" stimulus where the blurred "holes" in sine-wave carriers were of equal area to the blurred target ("cheese") regions. The locations of the target regions in the monocular image pairs were interdigitated across eyes such that their binocular sum was a uniform grating. When pedestal contrasts were above threshold, the monocular neural images contained strong evidence that the high-contrast regions in the two eyes did not overlap. Nevertheless, sensitivity to dual contrast increments (i.e., to contrast increments in different locations in the two eyes) was a factor of ∼1.7 greater than to single increments (i.e., increments in a single eye), comparable with conventional binocular summation. This provides evidence for a contiguous area summation process that operates at all contrasts and is influenced little, if at all, by eye of origin. A three-stage model of contrast gain control fitted the results and possessed the properties of ocularity invariance and area invariance owing to its cascade of normalization stages. The implications for a population code for pattern size are discussed.