Visual sensitivity, blur and the sources of variability in the amplitude spectra of natural scenes

Optical phase nullification partially restores visual and stereo acuity lost to simulated blur from higher-order wavefront aberrations of keratoconic eyes

Contrast demodulation and phase distortions are exaggerated in retinal images blurred by the higher-order wavefront aberrations of keratoconic eyes. While the performance loss from the former parameter is well understood, little is known about the impact of the latter on visual functions in this disease condition. The present study investigated the impact of phase distortions on the monocular logMAR visual acuity, letter discriminability and random-dot stereoacuity of seventeen visually healthy adults (ten for visual acuity and letter discriminability; ten for stereoacuity and three common to both experiments) using images that were computationally blurred by four different higher-order wavefront aberration profiles of keratoconic eyes that showed significant distortions in the phase spectrum. Participants viewed these images through 2 mm artificial pupils to negate their native ocular wavefront aberrations. The results showed progressive losses in visual acuity and stereoacuity with increasing blur, a third of which could be recovered following phase nullification. Letter discriminability also improved following phase nullification, more so for smaller than larger optotypes. Stereoacuity loss and, consequently, its recovery following phase nullification was more prominent for profiles simulating unilateral asymmetric keratoconus than for profiles simulating bilateral symmetric keratoconus. These results agree with previous reports obtained from blur induced with lower-order aberrations and indicate that a similar trend may be observed for more complex patterns of blur like keratoconus. Overall, both contrast demodulation and misalignment of the local features of the blurred image may contribute to losses of spatial and depth vision in keratoconus. Phase nullification may partially mitigate these losses, thereby allowing the processing of finer spatial details and veridical disparity estimations for improved depth perception.

Fractal Fluency: Processing of Fractal Stimuli Across Sight, Sound, and Touch

People are continually exposed to the rich complexity generated by the repetition of fractal patterns at different size scales. Fractals are prevalent in natural scenery and also in patterns generated by artists and mathematicians. In this chapter, we will investigate the powerful significance of fractals for the human senses. In particular, we propose that fractals with mid-range complexity play a unique role in our visual experiences because the visual system has adapted to these prevalent natural patterns. This adaptation is evident at multiple stages of the visual system, ranging from data acquisition by the eye to processing of this data in the higher visual areas of the brain. Based on these results, we will discuss a fluency model in which the visual system processes mid-complexity fractals with relative ease. This fluency optimizes the observer's capabilities (such as enhanced attention and pattern recognition) and generates an aesthetic experience accompanied by a reduction in the observer's physiological stress levels. In addition to reviewing people's responses to viewing fractals, we will compare these responses to recent research focused on fractal sounds and fractal surface textures. We will extend our fractal fluency model to allow for stimuli across multiple senses.

Fractal Phototherapy in Maximizing Retina and Brain Plasticity

The neuroplasticity potential is reduced with aging and impairs during neurodegenerative diseases and brain and visual system injuries. This limits the brain's capacity to repair the structure and dynamics of its activity after lesions. Maximization of neuroplasticity is necessary to provide the maximal CNS response to therapeutic intervention and adaptive reorganization of neuronal networks in patients with degenerative pathology and traumatic injury to restore the functional activity of the brain and retina.Considering the fractal geometry and dynamics of the healthy brain and the loss of fractality in neurodegenerative pathology, we suggest that the application of self-similar visual signals with a fractal temporal structure in the stimulation therapy can reactivate the adaptive neuroplasticity and enhance the effectiveness of neurorehabilitation. This proposition was tested in the recent studies. Patients with glaucoma had a statistically significant positive effect of fractal photic therapy on light sensitivity and the perimetric MD index, which shows that methods of fractal stimulation can be a novel nonpharmacological approach to neuroprotective therapy and neurorehabilitation. In healthy rabbits, it was demonstrated that a long-term course of photostimulation with fractal signals does not harm the electroretinogram (ERG) and retina structure. Rabbits with modeled retinal atrophy showed better dynamics of the ERG restoration during daily stimulation therapy for a week in comparison with the controls. Positive changes in the retinal function can indirectly suggest the activation of its adaptive plasticity and the high potential of stimulation therapy with fractal visual stimuli in a nonpharmacological neurorehabilitation, which requires further study.

Novel Morphological Profiling Assay Connects ex Vivo Endothelial Cell Responses to Disease Severity in Liver Cirrhosis

Background and Aims

Endothelial cell (EC) dysfunction in response to circulating plasma factors is a known causal factor in many systemic diseases. However, no appropriate assay is available to investigate this causality ex vivo. In liver cirrhosis, systemic inflammation is identified as central mechanism in progression from compensated to decompensated cirrhosis (DC), but the role of ECs therein is unknown. We aimed to develop a novel ex vivo assay for assessing EC responses to patient-derived plasma (PDP) and assess the potential of this assay in a cohort of liver cirrhosis patients.

Methods

Image-based morphological profiling was utilized to assess the impact of PDP on cultured ECs. Endothelial cell (EC) monolayers were exposed to 25% stabilized PDP (20 compensated cirrhoses, 20 DCs, and 20 healthy controls (HCs). Single-cell morphological profiles were extracted by automated image-analysis following staining of multiple cellular components and high-content imaging. Patient profiles were created by dimension reduction and cell-to-patient data aggregation, followed by multivariate-analysis to stratify patients and identify discriminating features.

Results

Patient-derived plasma (PDP) exposure induced profound changes in EC morphology, displaying clear differences between controls and DC patients. Compensated cirrhosis patients showed overlap with healthy controls and DC patients. Supervised analysis showed Child-Pugh (CP) class could be predicted from EC morphology. Most importantly, CP-C patients displayed distinct EC phenotypes, in which mitochondrial changes were most discriminative.

Conclusion

Morphological profiling presents a viable tool to assess the endothelium ex vivo. We demonstrated that the EC phenotype corresponds with disease severity in liver cirrhosis. Moreover, our results suggest the presence of mitochondrial dysfunction in ECs of CP-C patient.

A mechanistic account of visual discomfort

Much of the neural machinery of the early visual cortex, from the extraction of local orientations to contextual modulations through lateral interactions, is thought to have developed to provide a sparse encoding of contour in natural scenes, allowing the brain to process efficiently most of the visual scenes we are exposed to. Certain visual stimuli, however, cause visual stress, a set of adverse effects ranging from simple discomfort to migraine attacks, and epileptic seizures in the extreme, all phenomena linked with an excessive metabolic demand. The theory of efficient coding suggests a link between excessive metabolic demand and images that deviate from natural statistics. Yet, the mechanisms linking energy demand and image spatial content in discomfort remain elusive. Here, we used theories of visual coding that link image spatial structure and brain activation to characterize the response to images observers reported as uncomfortable in a biologically based neurodynamic model of the early visual cortex that included excitatory and inhibitory layers to implement contextual influences. We found three clear markers of aversive images: a larger overall activation in the model, a less sparse response, and a more unbalanced distribution of activity across spatial orientations. When the ratio of excitation over inhibition was increased in the model, a phenomenon hypothesised to underlie interindividual differences in susceptibility to visual discomfort, the three markers of discomfort progressively shifted toward values typical of the response to uncomfortable stimuli. Overall, these findings propose a unifying mechanistic explanation for why there are differences between images and between observers, suggesting how visual input and idiosyncratic hyperexcitability give rise to abnormal brain responses that result in visual stress.

Levels of orientation bias differ across digital content categories: Implications for visual perception

With the continued growth of digital device use, a greater portion of the visual world experienced daily by many people has shifted towards digital environments. The "oblique effect" denotes a bias for horizontal and vertical (canonical) contours over oblique contours, which is derived from a disproportionate exposure to canonical content. Carpentered environments have been shown to possess proportionally more canonical than oblique contours, leading to perceptual bias in those who live in "built" environments. Likewise, there is potential for orientation sensitivity to be shaped by frequent exposure to digital content. The potential influence of digital content on the oblique effect was investigated by measuring the degree of orientation anisotropy from a range of digital scenes using Fourier analysis. Content from popular cartoons, video games, and social communication websites was compared to real-life nature, suburban, and urban scenes. Findings suggest that digital content varies widely in orientation anisotropy, but pixelated video games and social communication websites were found to exhibit a degree of orientation anisotropy substantially exceeding that observed in all measured categories of real-world environments. Therefore, the potential may exist for digital content to induce an even greater shift in orientation bias than has been observed in previous research. This potential, and implications of such a shift, is discussed.

Virtual Reality for Vision Science

Virtual reality (VR) allows us to create visual stimuli that are both immersive and reactive. VR provides many new opportunities in vision science. In particular, it allows us to present wide field-of-view, immersive visual stimuli; for observers to actively explore the environments that we create; and for us to understand how visual information is used in the control of behaviour. In contrast with traditional psychophysical experiments, VR provides much greater flexibility in creating environments and tasks that are more closely aligned with our everyday experience. These benefits of VR are of particular value in developing our theories of the behavioural goals of the visual system and explaining how visual information is processed to achieve these goals. The use of VR in vision science presents a number of technical challenges, relating to how the available software and hardware limit our ability to accurately specify the visual information that defines our virtual environments and the interpretation of data gathered in experiments with a freely moving observer in a responsive environment.

Calibrating Vision: Concepts and Questions

The idea that visual coding and perception are shaped by experience and adjust to changes in the environment or the observer is universally recognized as a cornerstone of visual processing, yet the functions and processes mediating these calibrations remain in many ways poorly understood. In this article we review a number of facets and issues surrounding the general notion of calibration, with a focus on plasticity within the encoding and representational stages of visual processing. These include how many types of calibrations there are - and how we decide; how plasticity for encoding is intertwined with other principles of sensory coding; how it is instantiated at the level of the dynamic networks mediating vision; how it varies with development or between individuals; and the factors that may limit the form or degree of the adjustments. Our goal is to give a small glimpse of an enormous and fundamental dimension of vision, and to point to some of the unresolved questions in our understanding of how and why ongoing calibrations are a pervasive and essential element of vision.

Nature in motion: The tuning of the visual system to the spatiotemporal properties of natural scenes

Natural scenes contain several statistical regularities despite their superficially diverse appearances (e.g., mountains, rainforests, deserts). First, they exhibit a unique distribution of luminance intensities decreasing across spatial frequency, known as the 1/f^α amplitude spectrum (α ≈ 1). Additionally, natural scenes share consistent geometric properties, comprising similar densities of structure across multiple scales—a property classifying them as fractal (e.g., how the branching patterns of rivers and trees appear similar irrespective of scale). These two properties are intimately related and correlate strongly in natural scenes. However, research using thresholded noise images suggests that spatially, the human visual system is preferentially tuned to natural scene structure more so than 1/f^α spectra. It is currently unclear whether this dependency on natural geometry extends to the temporal domain. We used a psychophysics task to measure discrimination sensitivity toward two types of synthetic noise movies: gray scale and thresholded (N = 60). Each movie type shared the same geometric properties (measured fractal D), but substantially differing spectral properties (measured α). In both space and time, we observe a characteristic dependency on stimulus structure across movie types, with sensitivity peaking for stimuli with natural geometry despite having altered 1/f^α spectra. Although only measured behaviorally, our findings may imply that the neural processes underlying this tuning have developed to be sensitive to the most stable signal in our natural environment—structure (e.g., the structural properties of a tree are consistent from morning to night despite illumination changes across time points).

Sensitivity to the slope of the amplitude spectrum is dependent on the spectral slopes of recently viewed environments: A visual adaptation study in modified reality

Scenes contain many statistical regularities that could benefit visual processing if accounted for by the visual system. One such statistic is the orientation-averaged slope (α) of the amplitude spectrum of natural scenes. Human observers show different discrimination sensitivity to α: sensitivity is highest for α values between 1.0 and 1.2 and decreases as α is steepened or shallowed. The range of α for peak discrimination sensitivity is concordant with the average α of natural scenes, which may indicate that visual mechanisms are optimized to process information at α values commonly encountered in the environment. Here we explore the association between peak discrimination sensitivity and the most viewed αs in natural environments. Specifically, we verified whether discrimination sensitivity depends on the recently viewed environments. Observers were immersed, using a Head-Mounted Display, in an environment that was either unaltered or had its average α steepened or shallowed by 0.4. Discrimination thresholds were affected by the average shift in α, but this effect was most prominent following adaptation to a shallowed environment. We modeled these data with a Bayesian observer and explored whether a change in the prior or a change in the likelihood best explained the psychophysical effects. Change in discrimination thresholds following adaptation could be explained by a shift in the central tendency of the prior concordant with the shift of the environment, in addition to a change in the likelihood. Our findings suggest that expectations on the occurrence of α that result from a lifetime of exposure remain plastic and able to accommodate for the statistical structure of recently viewed environments.

What Happens in Your Brain When You Walk Down the Street? Implications of Architectural Proportions, Biophilia, and Fractal Geometry for Urban Science

This article reviews current research in visual urban perception. The temporal sequence of the first few milliseconds of visual stimulus processing sheds light on the historically ambiguous topic of aesthetic experience. Automatic fractal processing triggers initial attraction/avoidance evaluations of an environment’s salubriousness, and its potentially positive or negative impacts upon an individual. As repeated cycles of visual perception occur, the attractiveness of urban form affects the user experience much more than had been previously suspected. These perceptual mechanisms promote walkability and intuitive navigation, and so they support the urban and civic interactions for which we establish communities and cities in the first place. Therefore, the use of multiple fractals needs to reintegrate with biophilic and traditional architecture in urban design for their proven positive effects on health and well-being. Such benefits include striking reductions in observers’ stress and mental fatigue. Due to their costs to individual well-being, urban performance, environmental quality, and climatic adaptation, this paper recommends that nontraditional styles should be hereafter applied judiciously to the built environment.

Blur Representation in the Amblyopic Visual System Using Natural and Synthetic Images

Purpose

Amblyopia is diagnosed as a reduced acuity in an otherwise healthy eye, which indicates that the deficit is not happening in the eye, but in the brain. One suspected mechanism explaining these deficits is an elevated amount of intrinsic blur in the amblyopic visual system compared to healthy observers. This "internally produced blur" can be estimated by the "equivalent intrinsic blur method", which measures blur discrimination thresholds while systematically increasing the external blur in the physical stimulus. Surprisingly, amblyopes do not exhibit elevated intrinsic blur when measured with an edge stimulus. Given the fundamental ways in which they differ, synthetic stimuli, such as edges, are likely to generate contrasting blur perception compared to natural stimuli, such as pictures. Because our visual system is presumably tuned to process natural stimuli, testing artificial stimuli only could result in performances that are not ecologically valid.

Methods

We tested this hypothesis by measuring, for the first time, the perception of blur added to natural images in amblyopia and compared discrimination performance for natural images and synthetic edges in healthy and amblyopic groups.

Results

Our results demonstrate that patients with amblyopia exhibit higher levels of intrinsic blur than control subjects when tested on natural images. This difference was not observed when using edges.

Conclusions

Our results suggest that intrinsic blur is elevated in the visual system representing vision from the amblyopic eye and that distinct statistics of images can generate different blur perception.

Steady-state visual evoked potential responses predict visual discomfort judgements

It has been suggested that aesthetically pleasing stimuli are processed efficiently by the visual system, whereas uncomfortable stimuli are processed inefficiently. This study consists of a series of three experiments investigating this idea using a range of images of abstract artworks, photographs of natural scenes, and computer-generated stimuli previously shown to be uncomfortable. Subjective judgements and neural correlates were measured using electroencephalogram (EEG) (steady-state visual evoked potentials, SSVEPs). In addition, global image statistics (contrast, Fourier amplitude spectral slope and fractal dimension) were taken into account. When effects of physical image contrast were controlled, fractal dimension predicted discomfort judgements, suggesting the SSVEP response is more likely to be influenced by distribution of edges than the spectral slope. Importantly, when effects of physical contrast and fractal dimension were accounted for using linear mixed effects modelling, SSVEP responses predicted subjective judgements of images. Specifically, when stimuli were not matched for perceived contrast, there was a positive relationship between SSVEP responses and how pleasing a stimulus was judged to be, and conversely a negative relationship between discomfort and SSVEP response. This is significant as it shows that the neural responses in early visual areas contribute to the subjective (un)pleasantness of images, although the results of this study do not provide clear support for the theory of efficient coding as the cause of perceived pleasantness or discomfort of images, and so other explanations need to be considered.

Predicting blur visual discomfort for natural scenes by the loss of positional information

The perception of blur due to accommodation failures, insufficient optical correction or imperfect image reproduction is a common source of visual discomfort, usually attributed to an anomalous and annoying distribution of the image spectrum in the spatial frequency domain. In the present paper, this discomfort is related to a loss of the localization accuracy of the observed patterns. It is assumed, as a starting perceptual principle, that the visual system is optimally adapted to pattern localization in a natural environment. Thus, since the best possible accuracy of the image patterns localization is indicated by the positional Fisher Information, it is argued that blur discomfort is strictly related to a loss of this information. Following this concept, a receptive field functional model is adopted to predict the visual discomfort. It is a complex-valued operator, orientation-selective both in the space domain and in the spatial frequency domain. Starting from the case of Gaussian blur, the analysis is extended to a generic type of blur by applying a positional Fisher Information equivalence criterion. Out-of-focus blur and astigmatic blur are presented as significant examples. The validity of the proposed model is verified by comparing its predictions with subjective ratings. The model fits linearly with the experiments reported in independent databases, based on different protocols and settings.

A new stationary grid, with grid lines aligned to pixel lines with submicron-order precision, to suppress grid artifacts

PURPOSE

We have developed a new stationary grid named a pixel-aligned grid (PA grid), in which the grid lines are aligned to the pixel lines with submicron-order precision. Further, we have evaluated its performance relative to that of a conventional grid combined with grid-line removal (GLR) processing.

METHODS

A flat-panel detector system of an indirect type, with a pixel pitch of 150 μm, was employed. Four PA grids having a grid ratio of 6:1 associated with abdominal bedside radiography, with the grid-line pitch (GP) varied around the target value of 150 μm, were produced. Blank images were obtained with four PA grids for measuring the period and amplitude of the grid artifact. In performance evaluation, acrylic and anthropomorphic abdominal phantom images were used with the PA grid, a conventional grid (40 lines/cm, grid ratio 6:1), and no grids. The grid artifacts were evaluated by power spectrum (PS) analysis. Also, the signal-to-noise ratio (SNR) improvement factor (K_SNR ) was measured.

RESULTS

Grid artifacts were hardly recognizable with PA grids with GP errors of 0.3 μm and 0.6 μm because of the prolonged grid artifact periods. The measured artifact amplitudes of these PA grids were less than 0.6%. Furthermore, the PA grids did not produce notable frequency peaks in PS. In contrast, the conventional grid without GLR processing produced two conspicuous peaks. With GLR processing, notable reductions in PS were observed around the two peak frequencies, which caused blurring in bone structures. For the acrylic thickness of 20 cm, the K_SNR s for the PA grid were around 1.4, suggesting some SNR improvement in abdominal bedside radiography.

CONCLUSION

The present study has demonstrated that PA grids with their grid-line pitches close to the pixel-line pitch within errors of 0.6 μm produce grid artifact-free images without any signal losses. Thus, the proposed PA grid will prove to be effective and useful in various clinical applications.

Do Humans and Deep Convolutional Neural Networks Use Visual Information Similarly for the Categorization of Natural Scenes?

The investigation of visual categorization has recently been aided by the introduction of deep convolutional neural networks (CNNs), which achieve unprecedented accuracy in picture classification after extensive training. Even if the architecture of CNNs is inspired by the organization of the visual brain, the similarity between CNN and human visual processing remains unclear. Here, we investigated this issue by engaging humans and CNNs in a two-class visual categorization task. To this end, pictures containing animals or vehicles were modified to contain only low/high spatial frequency (HSF) information, or were scrambled in the phase of the spatial frequency spectrum. For all types of degradation, accuracy increased as degradation was reduced for both humans and CNNs; however, the thresholds for accurate categorization varied between humans and CNNs. More remarkable differences were observed for HSF information compared to the other two types of degradation, both in terms of overall accuracy and image-level agreement between humans and CNNs. The difficulty with which the CNNs were shown to categorize high-passed natural scenes was reduced by picture whitening, a procedure which is inspired by how visual systems process natural images. The results are discussed concerning the adaptation to regularities in the visual environment (scene statistics); if the visual characteristics of the environment are not learned by CNNs, their visual categorization may depend only on a subset of the visual information on which humans rely, for example, on low spatial frequency information.

What is visible across the visual field?

It is sometimes claimed that because the resolution and sensitivity of visual perception are better in the fovea than in the periphery, peripheral vision cannot support the same kinds of colour and sharpness percepts as foveal vision. The fact that a scene nevertheless seems colourful and sharp throughout the visual field then poses a puzzle. In this study, I use a detailed model of human spatial vision to estimate the visibility of certain properties of natural scenes, including aspects of colourfulness, sharpness, and blurriness, across the visual field. The model is constructed to reproduce basic aspects of human contrast and colour sensitivity over a range of retinal eccentricities. I apply the model to colourful, complex natural scene images, and estimate the degree to which colour and edge information are present in the model's representation of the scenes. I find that, aside from the intrinsic drift in the spatial scale of the representation, there are not large qualitative differences between foveal and peripheral representations of 'colourfulness' and 'sharpness'.

Priming with skin-problems increases fear of clusters

Trypophobia is induced by viewing multiple clustered objects. To date, several studies have investigated why certain people experience discomfort when looking at clustered patterns. Recently, “involuntary protection against dermatosis” (IPAD) hypothesis was proposed to explain the causes of trypophobia. The IPAD hypothesis suggests that involuntary aversive responses to skin diseases cause discomfort in response to image clusters. However, this idea has not been fully investigated empirically. Therefore, the present study used a modified version of the priming procedure and tested whether the activation of the concept of skin-related diseases affected the evaluation of trypophobic images. In Experiment 1, participants engaged in a lexical decision task in which words related to skin problems, negative events, or neutral events were presented. Then, they evaluated the discomfort of trypophobic, negative, and neutral images. The results indicated that participants evaluated trypophobic images as more discomforting after they were exposed to skin-problem-related words, whereas the exposure to words related to skin-problems did not enhance the discomfort of negative images. These findings demonstrate that the association with skin-related problems increases the discomfort of trypophobic images. In Experiment 2, we further tested the reproducibility of the priming effect observed in Experiment 1 and investigated the effect of priming with words related to COVID-19 in the context of a spreading infection. Contrary to predictions, no priming effect was produced by either skin-related words or COVID-19-related words. Future studies should further explore the causal relationship of the association between skin disease and trypophobia.

The Potential of Biophilic Fractal Designs to Promote Health and Performance: A Review of Experiments and Applications

Fractal objects are prevalent in natural scenery. Their repetition of patterns at increasingly fine magnifications creates a rich complexity. Fractals displaying mid-range complexity are the most common and include trees, clouds, and mountains. The “fractal fluency” model states that human vision has adapted to process these mid-range fractals with ease. I will first discuss fractal fluency and demonstrate how it enhances the observer’s visual capabilities by focusing on experiments that have important practical consequences for improving the built environment. These enhanced capabilities generate an aesthetic experience and physiological stress reduction. I will discuss strategies for integrating fractals into building designs to induce positive impacts on the observer. Examples include fractal solar panels, fractal window shades, and fractal floor patterns. These applications of fractal fluency represent a fundamental and potentially impactful form of salutogenesis.

Autofocusing technologies for whole slide imaging and automated microscopy

Whole slide imaging (WSI) has moved digital pathology closer to diagnostic practice in recent years. Due to the inherent tissue topography variability, accurate autofocusing remains a critical challenge for WSI and automated microscopy systems. The traditional focus map surveying method is limited in its ability to acquire a high degree of focus points while still maintaining high throughput. Real-time approaches decouple image acquisition from focusing, thus allowing for rapid scanning while maintaining continuous accurate focus. This work reviews the traditional focus map approach and discusses the choice of focus measure for focal plane determination. It also discusses various real-time autofocusing approaches including reflective-based triangulation, confocal pinhole detection, low-coherence interferometry, tilted sensor approach, independent dual sensor scanning, beam splitter array, phase detection, dual-LED illumination and deep-learning approaches. The technical concepts, merits and limitations of these methods are explained and compared to those of a traditional WSI system. This review may provide new insights for the development of high-throughput automated microscopy imaging systems that can be made broadly available and utilizable without loss of capacity.

Testing impacts of global blur profiles using a multiscale vision simulator

Although it is possible to specify the impact of blur at a specific retinal location, a lack of understanding exists regarding how the inhomogeneous blur distribution across the retina (i.e., global blur) affects the quality of an optical correction at a specific retinal location. To elucidate this issue, a multiscale visual simulator combining the projection of a controllable high-resolution stimulus and an ocular monitoring system was constructed to simultaneously simulate foveal and extrafoveal blurs. To define the range and capability of a wide-angle stimulation, an optimal working pupil was evaluated by optical ray-tracing via a Monte Carlo simulation, including optical variations corresponding to fixational eye movements. To investigate the impacts of global blur on the perception of discrete regions of the visual field, the bothersome blur threshold from five subjects was measured through this novel system using a collection of zonal blurs (annuli image projected sequentially at discrete retinal regions), and these impacts were compared with those using a spatially-varying blur (continuum of simultaneously projected zonal blurs of varying strengths, simulating retinal blur variations). Our results show that the zonal blur threshold does not entirely predict the global blur threshold, having a tendency to overestimate blur the threshold. It was concluded that, in addition to the amount of defocus present at a defined retinal location, the perception of individual defocused retinal regions can be affected by global blur. Given that blur tolerance can affect the perception of optically induced blurs, the findings provide useful implications for designing new optical correction.

Focus Quality Assessment of High-Throughput Whole Slide Imaging in Digital Pathology

One of the challenges facing the adoption of digital pathology workflows for clinical use is the need for automated quality control. As the scanners sometimes determine focus inaccurately, the resultant image blur deteriorates the scanned slide to the point of being unusable. Also, the scanned slide images tend to be extremely large when scanned at greater or equal 20X image resolution. Hence, for digital pathology to be clinically useful, it is necessary to use computational tools to quickly and accurately quantify the image focus quality and determine whether an image needs to be re-scanned. We propose a no-reference focus quality assessment metric specifically for digital pathology images that operate by using a sum of even-derivative filter bases to synthesize a human visual system-like kernel, which is modeled as the inverse of the lens' point spread function. This kernel is then applied to a digital pathology image to modify high-frequency image information deteriorated by the scanner's optics and quantify the focus quality at the patch level. We show in several experiments that our method correlates better with ground-truth z -level data than other methods, which is more computationally efficient. We also extend our method to generate a local slide-level focus quality heatmap, which can be used for automated slide quality control, and demonstrate the utility of our method for clinical scan quality control by comparison with subjective slide quality scores.

Convolutional Deblurring for Natural Imaging

In this paper, we propose a novel design of image deblurring in the form of one-shot convolution filtering that can directly convolve with naturally blurred images for restoration. The problem of optical blurring is a common disadvantage to many imaging applications that suffer from optical imperfections. Despite numerous deconvolution methods that blindly estimate blurring in either inclusive or exclusive forms, they are practically challenging due to high computational cost and low image reconstruction quality. Both conditions of high accuracy and high speed are prerequisites for high-throughput imaging platforms in digital archiving. In such platforms, deblurring is required after image acquisition before being stored, previewed, or processed for high-level interpretation. Therefore, on-the-fly correction of such images is important to avoid possible time delays, mitigate computational expenses, and increase image perception quality. We bridge this gap by synthesizing a deconvolution kernel as a linear combination of finite impulse response (FIR) even-derivative filters that can be directly convolved with blurry input images to boost the frequency fall-off of the point spread function (PSF) associated with the optical blur. We employ a Gaussian low-pass filter to decouple the image denoising problem for image edge deblurring. Furthermore, we propose a blind approach to estimate the PSF statistics for two Gaussian and Laplacian models that are common in many imaging pipelines. Thorough experiments are designed to test and validate the efficiency of the proposed method using 2054 naturally blurred images across six imaging applications and seven state-of-the-art deconvolution methods.

No-Reference Quality Assessment Method for Blurriness of SEM Micrographs with Multiple Texture

Scanning electron microscopy (SEM) plays an important role in the intuitive understanding of microstructures because it can provide ultrahigh magnification. Tens or hundreds of images are regularly generated and saved during a typical microscopy imaging process. Given the subjectivity of a microscopist's focusing operation, blurriness is an important distortion that debases the quality of micrographs. The selection of high-quality micrographs using subjective methods is expensive and time-consuming. This study proposes a new no-reference quality assessment method for evaluating the blurriness of SEM micrographs. The human visual system is more sensitive to the distortions of cartoon components than to those of redundant textured components according to the Gestalt perception psychology and the entropy masking property. Micrographs are initially decomposed into cartoon and textured components. Then, the spectral and spatial sharpness maps of the cartoon components are extracted. One metric is calculated by combining the spatial and spectral sharpness maps of the cartoon components. The other metric is calculated on the basis of the edge of the maximum local variation map of the cartoon components. Finally, the two metrics are combined as the final metric. The objective scores generated using this method exhibit high correlation and consistency with the subjective scores.

Image statistics of the environment surrounding freely behaving hoverflies

Natural scenes are not as random as they might appear, but are constrained in both space and time. The 2-dimensional spatial constraints can be described by quantifying the image statistics of photographs. Human observers perceive images with naturalistic image statistics as more pleasant to view, and both fly and vertebrate peripheral and higher order visual neurons are tuned to naturalistic image statistics. However, for a given animal, what is natural differs depending on the behavior, and even if we have a broad understanding of image statistics, we know less about the scenes relevant for particular behaviors. To mitigate this, we here investigate the image statistics surrounding Episyrphus balteatus hoverflies, where the males hover in sun shafts created by surrounding trees, producing a rich and dense background texture and also intricate shadow patterns on the ground. We quantified the image statistics of photographs of the ground and the surrounding panorama, as the ventral and lateral visual field is particularly important for visual flight control, and found differences in spatial statistics in photos where the hoverflies were hovering compared to where they were flying. Our results can, in the future, be used to create more naturalistic stimuli for experimenter-controlled experiments in the laboratory.

Encoding Visual Sensitivity by MaxPol Convolution Filters for Image Sharpness Assessment

In this paper, we propose a novel design of Human Visual System (HVS) response in a convolutional filter form to decompose meaningful features that are closely tied with image sharpness level. No-reference (NR) Image sharpness assessment (ISA) techniques have emerged as the standard of image quality assessment in diverse imaging applications. Despite their high correlation with subjective scoring, they are challenging for practical considerations due to high computational cost and lack of scalability across different image blurs. We bridge this gap by synthesizing the HVS response as a linear combination of Finite Impulse Response (FIR) derivative filters to boost the falloff of high band frequency magnitudes in natural imaging paradigm. The numerical implementation of the HVS filter is carried out with MaxPol filter library that can be arbitrarily set for any differential orders and cutoff frequencies to balance out the estimation of informative features and noise sensitivities. Utilized by HVS filter, we then design an innovative NR-ISA metric called "HVS-MaxPol" that (a) requires minimal computational cost, (b) produce high correlation accuracy with image sharpness level, and (c) scales to assess synthetic and natural image blur. Specifically, the synthetic blur images are constructed by blurring the raw images using Gaussian filter, while natural blur is observed from real-life application such as motion, out-of-focus, luminance contrast, etc. Furthermore, we create a natural benchmark database in digital pathology for validation of image focus quality in whole slide imaging systems called "FocusPath" consisting of 864 blurred images. Thorough experiments are designed to test and validate the efficiency of HVS-MaxPol across different blur databases and state-of-the-art NR-ISA metrics. The experiment result indicates that our metric has the best overall performance with respect to speed, accuracy and scalability.

Acute sleep loss induces signs of visual discomfort in young men

Acute sleep loss influences visual processes in humans, such as recognizing facial emotions. However, to the best of our knowledge, no study till date has examined whether acute sleep loss alters visual comfort when looking at images. One image statistic that can be used to investigate the level of visual comfort experienced under visual encoding is the slope of the amplitude spectrum, also referred to as the slope constant. The slope constant describes the spatial distribution of pixel intensities and deviations from the natural slope constant can induce visual discomfort. In the present counterbalanced crossover design study, 11 young men with normal or corrected‐to‐normal vision participated in two experimental conditions: one night of sleep loss and one night of sleep. In the morning after each intervention, subjects performed a computerized psychophysics task. Specifically, they were required to adjust the slope constant of images depicting natural landscapes and close‐ups with a randomly chosen initial slope constant until they perceived each image as most natural looking. Subjects also rated the pleasantness of each selected image. Our analysis showed that following sleep loss, higher slope constants were perceived as most natural looking when viewing images of natural landscapes. Images with a higher slope constant are generally perceived as blurrier. The selected images were also rated as less pleasant after sleep loss. No such differences between the experimental conditions were noted for images of close‐ups. The results suggest that sleep loss induces signs of visual discomfort in young men. Possible implications of these findings are discussed.

Trypophobic images gain preferential access to early visual processes

Trypophobia is a common but unusual phobia that is induced by viewing many clustered objects. Previous studies suggested that this trypophobia is caused by the specific power spectrum of the images; this idea has not been fully investigated empirically. In the present study, we used breaking continuous flash suppression (b-CFS) to clarify whether the trypophobic images affect access to visual awareness, and what features of trypophobic images contribute to rapid access of awareness. In the b-CFS paradigms, a dynamic masking pattern presented to one eye suppresses the target images shown to the other eye. The participants' task was to indicate where the target image appeared in a dichoptic display through a mirror stereoscope. The target images consisted of trypophobic, fear-related, clusters or neutral images. The trypophobic images emerged into awareness faster than the other types of images. However, the phase-scrambled versions of the trypophobic images did not show any differences across the image types, suggesting that the trypophobic power spectra themselves did not affect access to awareness. Moreover, the phase-scrambled trypophobic images without CFS tended to be detected earlier than the phase-scrambled fearful and neutral images. These findings indicate that trypophobic power spectra might affect post-perceptual processing, such as response production.

Trypophobic images induce oculomotor capture and inhibition

It is known that unpleasant images capture our attention. However, the causes of the emotions evoked by these images can vary. Trypophobia is the fear of clustered objects. A recent study claimed that this phobia is elicited by the specific power spectrum of such images. In the present study, we measured saccade trajectories to examine how trypophobic images possessing a characteristic power spectrum affect visual attention. The participants' task was to make a saccade in the direction that was indicated by a cue. Four irrelevant images with different emotional content were presented as periphery distractors at 0 ms, 150 ms, and 450 ms in terms of cue-image onset asynchrony. The irrelevant images consisted of trypophobic, fearful, or neutral scenes. The presence of saccade trajectory deviations induced by trypophobic images suggest that intact trypophobic images oriented attention to their location. Moreover, when the images were phase scrambled, the saccade curved away from the trypophobic images, suggesting that trypophobic power spectra also triggered attentional capture, which was weak and then led to inhibition. These findings suggest that not only the power spectral characteristics but also the gist of a trypophobic image affect attentional deployment.

Screening of Drug-Transporter Interactions in a 3D Microfluidic Renal Proximal Tubule on a Chip

Drug-transporter interactions could impact renal drug clearance and should ideally be detected in early stages of drug development to avoid toxicity-related withdrawals in later stages. This requires reliable and robust assays for which current high-throughput screenings have, however, poor predictability. Kidney-on-a-chip platforms have the potential to improve predictability, but often lack compatibility with high-content detection platforms. Here, we combined conditionally immortalized proximal tubule epithelial cells overexpressing organic anion transporter 1 (ciPTEC-OAT1) with the microfluidic titer plate OrganoPlate to develop a screenings assay for renal drug-transporter interactions. In this platform, apical localization of F-actin and intracellular tight-junction protein zonula occludens-1 (ZO-1) indicated appropriate cell polarization. Gene expression levels of the drug transporters organic anion transporter 1 (OAT1; SLC22A6), organic cation transporter 2 (OCT2; SLC22A2), P-glycoprotein (P-gp; ABCB1), and multidrug resistance-associated protein 2 and 4 (MRP2/4; ABCC2/4) were similar levels to 2D static cultures. Functionality of the efflux transporters P-gp and MRP2/4 was studied as proof-of-concept for 3D assays using calcein-AM and 5-chloromethylfluorescein-diacetate (CMFDA), respectively. Confocal imaging demonstrated a 4.4 ± 0.2-fold increase in calcein accumulation upon P-gp inhibition using PSC833. For MRP2/4, a 3.0 ± 0.2-fold increased accumulation of glutathione-methylfluorescein (GS-MF) was observed upon inhibition with a combination of PSC833, MK571, and KO143. Semi-quantitative image processing methods for P-gp and MRP2/4 was demonstrated with corresponding Z'-factors of 0.1 ± 0.3 and 0.4 ± 0.1, respectively. In conclusion, we demonstrate a 3D microfluidic PTEC model valuable for screening of drug-transporter interactions that further allows multiplexing of endpoint read-outs for drug-transporter interactions and toxicity.

Practice makes the deficiency of global motion detection in people with pattern-related visual stress more apparent

Aims

Pattern-related visual stress (PRVS) refers to the perceptual difficulties experienced by some individuals when exposed to high contrast striped patterns. People with PRVS were reported to have reduced sensitivity to global motion at baseline testing and the difference disappears at a second estimate. The present study was to investigate the effect of practice on global motion threshold in adults with and without PRVS.

Methods

A total of 101 subjects were recruited and the Wilkins & Evans Pattern Glare Test was used to determine if a subject had PRVS. The threshold to detect global motion was measured with a random dot kinematogram. Each subject was measured 5 times at the first visit and again a month later. Receiver operating characteristic (ROC) curve analysis was applied to show the agreement between the two tests.

Results

Twenty-nine subjects were classified as having PRVS and 72 were classified as normal. At baseline, the threshold to detect global motion was significantly higher in subjects with PRVS (0.832 ± 0.098 vs. 0.618 ± 0.228, p < 0.001). After 5 sessions, the difference between the normal and subjects with PRVS increased (0.767 ± 0.170 vs. 0.291 ± 0.149, p < 0.001). In ROC analysis, the area under the curve (AUC) improved from 0.792 at baseline to 0.964 at the fifth session. After a one-month break, the difference between normal and subjects with PRVS was still significant (0.843 ± 0.169 vs. 0.407 ± 0.216, p < 0.001) and the AUC was 0.875.

Conclusion

The ability to detect global motion is impaired in persons with PRVS and the difference increased after additional sessions of practice.

Visual adaptation and the amplitude spectra of radiological images

We examined how visual sensitivity and perception are affected by adaptation to the characteristic amplitude spectra of X-ray mammography images. Because of the transmissive nature of X-ray photons, these images have relatively more low-frequency variability than natural images, a difference that is captured by a steeper slope of the amplitude spectrum (~ − 1.5) compared to the ~ 1/f (slope of − 1) spectra common to natural scenes. Radiologists inspecting these images are therefore exposed to a different balance of spectral components, and we measured how this exposure might alter spatial vision. Observers (who were not radiologists) were adapted to images of normal mammograms or the same images sharpened by filtering the amplitude spectra to shallower slopes. Prior adaptation to the original mammograms significantly biased judgments of image focus relative to the sharpened images, demonstrating that the images are sufficient to induce substantial after-effects. The adaptation also induced strong losses in threshold contrast sensitivity that were selective for lower spatial frequencies, though these losses were very similar to the threshold changes induced by the sharpened images. Visual search for targets (Gaussian blobs) added to the images was also not differentially affected by adaptation to the original or sharper images. These results complement our previous studies examining how observers adapt to the textural properties or phase spectra of mammograms. Like the phase spectrum, adaptation to the amplitude spectrum of mammograms alters spatial sensitivity and visual judgments about the images. However, unlike the phase spectrum, adaptation to the amplitude spectra did not confer a selective performance advantage relative to more natural spectra.

Objective Quality Assessment and Perceptual Compression of Screen Content Images

Screen content image (SCI) has recently emerged as an active topic due to the rapidly increasing demand in many graphically rich services such as wireless displays and virtual desktops. SCIs are often composed of pictorial regions and computer generated textual/graphical content, which exhibit different statistical properties that often lead to different viewer behaviors. Inspired by this, we propose an objective quality assessment approach for SCIs that incorporates both visual field adaptation and information content weighting into structural similarity based local quality assessment. Furthermore, we develop a perceptual screen content coding scheme based on the newly proposed quality assessment measure, targeting at further improving the SCI compression performance. Experimental results show that the proposed quality assessment method not only better predicts the perceptual quality of SCIs, but also demonstrates great potentials in the design of perceptually optimal SCI compression schemes.

Neuronal mechanisms underlying differences in spatial resolution between darks and lights in human vision

Artists and astronomers noticed centuries ago that humans perceive dark features in an image differently from light ones; however, the neuronal mechanisms underlying these dark/light asymmetries remained unknown. Based on computational modeling of neuronal responses, we have previously proposed that such perceptual dark/light asymmetries originate from a luminance/response saturation within the ON retinal pathway. Consistent with this prediction, here we show that stimulus conditions that increase ON luminance/response saturation (e.g., dark backgrounds) or its effect on light stimuli (e.g., optical blur) impair the perceptual discrimination and salience of light targets more than dark targets in human vision. We also show that, in cat visual cortex, the magnitude of the ON luminance/response saturation remains relatively constant under a wide range of luminance conditions that are common indoors, and only shifts away from the lowest luminance contrasts under low mesopic light. Finally, we show that the ON luminance/response saturation affects visual salience mostly when the high spatial frequencies of the image are reduced by poor illumination or optical blur. Because both low luminance and optical blur are risk factors in myopia, our results suggest a possible neuronal mechanism linking myopia progression with the function of the ON visual pathway.

Image statistics and their processing in insect vision

Natural scenes may appear random, but are not only constrained in space and time, but also show strong spatial and temporal correlations. Spatial constraints and correlations can be described by quantifying image statistics, which include intuitive measures such as contrast, color and luminance, but also parameters that need some type of transformation of the image. In this review we will discuss some common tools used to quantify spatial and temporal parameters of naturalistic visual input, and how these tools have been used to inform us about visual processing in insects. In particular, we will review findings that would not have been possible using conventional, experimenter defined stimuli.

Data-analysis strategies for image-based cell profiling

Image-based cell profiling is a high-throughput strategy for the quantification of phenotypic differences among a variety of cell populations. It paves the way to studying biological systems on a large scale by using chemical and genetic perturbations. The general workflow for this technology involves image acquisition with high-throughput microscopy systems and subsequent image processing and analysis. Here, we introduce the steps required to create high-quality image-based (i.e., morphological) profiles from a collection of microscopy images. We recommend techniques that have proven useful in each stage of the data analysis process, on the basis of the experience of 20 laboratories worldwide that are refining their image-based cell-profiling methodologies in pursuit of biological discovery. The recommended techniques cover alternatives that may suit various biological goals, experimental designs, and laboratories' preferences.

A Delphi study to develop practical diagnostic guidelines for visual stress (pattern-related visual stress)

PURPOSE

Visual stress (VS) is characterised by symptoms of visual perceptual distortions and eyestrain when viewing text, symptoms that are alleviated by individually prescribed coloured filters. A recent review supports the existence of VS and its treatment, but noted that controversy remains, in part due to inconsistencies in the diagnosis of the condition. The present paper reviews the diagnostic criteria for VS in the literature and reports a Delphi analysis of the criteria currently used in clinical practice.

METHODS

Twenty-six eyecare practitioners were invited to participate in a Delphi study. They were selected because they were frequent prescribers of precision tinted lenses. In the first round they were sent a list of the indicators for which there is literature to suggest a relevance in the diagnosis of VS. The practitioners were invited to rank the indicators and add any additional criteria they use in diagnosis. In the second round a revised list was circulated, including items added from the responses in the first round.

RESULTS

The respondents included optometrists, orthoptists and opticians. In the first round the response rate was 85%. Ninety-one percent of those who participated in the first round also responded in the second round. Strong indicators in the second round included the symptom of words moving when reading, voluntary use of an overlay for a prolonged period, improved performance of ≥15% with an overlay on the Wilkins Rate of Reading test, and an abnormally high score on the Pattern Glare Test.

CONCLUSIONS

The strongest diagnostic criteria are combined in a diagnostic tool. This is proposed as a guide for clinical practice and further research.

Combining 1-D components to extract pattern information: It is about more than component similarity

At least under some conditions, plaid stimuli are processed by combining information first extracted in orientation and scale-selective channels. The rules that govern this combination across channels are only partially understood. Although the available data suggests that only components having similar spatial frequency and contrast are combined, the extent to which this holds has not been firmly established. To address this question, we measured, in human subjects, the short-latency reflexive vergence eye movements induced by stereo plaids in which spatial frequency and contrast of the components are independently varied. We found that, although similarity in component spatial frequency and contrast matter, they interact in a nonseparable way. One way in which this relationship might arise is if the internal estimate of contrast is not a faithful representation of stimulus contrast but is instead spatial frequency–dependent (with higher spatial frequencies being boosted). We propose that such weighting might have been put in place by a mechanism that, in an effort of achieve contrast constancy and/or coding efficiency, regulates the gain of detectors in early visual cortex to equalize their long-term average response to natural images.

The tuning of human visual cortex to variations in the 1/fα amplitude spectra and fractal properties of synthetic noise images

Natural scenes share a consistent distribution of energy across spatial frequencies (SF) known as the 1/f^α amplitude spectrum (α≈0.8-1.5, mean 1.2). This distribution is scale-invariant, which is a fractal characteristic of natural scenes with statistically similar structure at different spatial scales. While the sensitivity of the visual system to the 1/f properties of natural scenes has been studied extensively using psychophysics, relatively little is known about the tuning of cortical responses to these properties. Here, we use fMRI and retinotopic mapping techniques to measure and analyze BOLD responses in early visual cortex (V1, V2, and V3) to synthetic noise images that vary in their 1/f^α amplitude spectra (α=0.25 to 2.25, step size: 0.50) and contrast levels (10% and 30%) (Experiment 1). To compare the dependence of the BOLD response between the photometric (intensity based) and geometric (fractal) properties of our stimuli, in Experiment 2 we compared grayscale noise images to their binary (thresholded) counterparts, which contain only black and white regions. In both experiments, early visual cortex responded maximally to stimuli generated to have an input 1/f slope corresponding to natural 1/f^α amplitude spectra, and lower BOLD responses were found for steeper or shallower 1/f slopes (peak modulation: 0.59% for 1.25 vs. 0.31% for 2.25). To control for changing receptive field sizes, responses were also analyzed across multiple eccentricity bands in cortical surface space. For most eccentricity bands, BOLD responses were maximal for natural 1/f^α amplitude spectra, but importantly there was no difference in the BOLD response to grayscale stimuli and their corresponding thresholded counterparts. Since the thresholding of an image changes its measured 1/f slope (α) but not its fractal characteristics, this suggests that neuronal responses in early visual cortex are not strictly driven by spectral slope values (photometric properties) but rather their embedded geometric, fractal-like scaling properties.

Just Noticeable Difference Estimation for Screen Content Images

We propose a novel just noticeable difference (JND) model for a screen content image (SCI). The distinct properties of the SCI result in different behaviors of the human visual system when viewing the textual content, which motivate us to employ a local parametric edge model with an adaptive representation of the edge profile in JND modeling. In particular, we decompose each edge profile into its luminance, contrast, and structure, and then evaluate the visibility threshold in different ways. The edge luminance adaptation, contrast masking, and structural distortion sensitivity are studied in subjective experiments, and the final JND model is established based on the edge profile reconstruction with tolerable variations. Extensive experiments are conducted to verify the proposed JND model, which confirm that it is accurate in predicting the JND profile, and outperforms the state-of-the-art schemes in terms of the distortion masking ability. Furthermore, we explore the applicability of the proposed JND model in the scenario of perceptually lossless SCI compression, and experimental results show that the proposed scheme can outperform the conventional JND guided compression schemes by providing better visual quality at the same coding bits.

Image Quality Ranking Method for Microscopy

Automated analysis of microscope images is necessitated by the increased need for high-resolution follow up of events in time. Manually finding the right images to be analyzed, or eliminated from data analysis are common day-to-day problems in microscopy research today, and the constantly growing size of image datasets does not help the matter. We propose a simple method and a software tool for sorting images within a dataset, according to their relative quality. We demonstrate the applicability of our method in finding good quality images in a STED microscope sample preparation optimization image dataset. The results are validated by comparisons to subjective opinion scores, as well as five state-of-the-art blind image quality assessment methods. We also show how our method can be applied to eliminate useless out-of-focus images in a High-Content-Screening experiment. We further evaluate the ability of our image quality ranking method to detect out-of-focus images, by extensive simulations, and by comparing its performance against previously published, well-established microscopy autofocus metrics.

Incomplete Figure Perception and Invisible Masking

The Gollin test (measuring recognition thresholds for fragmented line drawings of everyday objects and animals) has traditionally been regarded as a test of incomplete figure perception or ‘closure’, though there is a debate about how such closure is achieved. Here, figural incompleteness is considered to be the result of masking, such that absence of contour elements of a fragmented figure is the result of the influence of an ‘invisible’ mask. It is as though the figure is partly obscured by a mask having parameters identical to those of the background. This mask is ‘invisible’ only consciously, but for the early stages of visual processing it is real and has properties of multiplicative noise. Incomplete Gollin figures were modeled as the figure covered by the mask with randomly distributed transparent and opaque patches. We adjusted the statistical characteristics of the contour image and empty noise patches and processed those using spatial and spatial-frequency measures. Across 73 figures, despite inter-subject variability, mean recognition threshold was always approximately 15% of total contour in naive observers. Recognition worsened with increasing spectral similarity between the figure and the ‘invisible’ mask. Near threshold, the spectrum of the fragmented image was equally similar to that of the ‘invisible’ mask and complete image. The correlation between spectral parameters of figures at threshold and complete figures was greatest for figures that were most easily recognised. Across test sessions, thresholds reduced when either figure or mask parameters were familiar. We argue that recognition thresholds for Gollin stimuli in part reflect the extraction of signal from noise.

Illusory Bands in Orientation and Spatial Frequency: A Cortical Analog to Mach Bands

Illusory bands at a luminance transition in space (ie an edge) are well known. Here we demonstrate illusory bands of enhanced orientations or spatial frequencies at transitions between higher-contrast and lower-contrast image content along the orientation and spatial-frequency dimensions—the dimensions of cortical spatial coding. We conclude that this illusion is a consequence of cortical-level suppression of units of similar orientations and spatial frequencies and serves to aid texture segmentation while providing efficient neural coding.

Structural Content in Paintings II: Artists Commissioned to Reproduce a Specific Image Over-Regularize Orientation Biases in Their Paintings

Measurements of psychophysical performance show that the visual system is biased in ways that counteract statistical regularities of natural scenes thereby allowing efficient coding. Here we consider the perceptual effects of these encoding biases in a “holistic” way by measuring characteristics of the paintings produced by artists making perceptual matches to a natural scene image; 10 artists were asked to produce an exact copy of a single outdoor landscape scene. The structural content of the paintings produced and the “ground truth” image were compared in the frequency domain. The artists were found to over-regularize the orientation content in the paintings: The anisotropy existing only at the lowest spatial scales in the natural scene image was produced across all spatial scales in these commissioned paintings. These results were compared to those from two other methods of comparing paintings and natural scenes reported previously in a companion paper and all three methodologies indicate very similar over-regularization. We suggest that artists may have a general canonical representation of structural relations of scenes that they apply broadly within their creations.

You Don't See What I See: Individual Differences in the Perception of Meaning from Visual Stimuli

Everyone has their own unique version of the visual world and there has been growing interest in understanding the way that personality shapes one's perception. Here, we investigated meaningful visual experiences in relation to the personality dimension of schizotypy. In a novel approach to this issue, a non-clinical sample of subjects (total n = 197) were presented with calibrated images of scenes, cartoons and faces of varying visibility embedded in noise; the spatial properties of the images were constructed to mimic the natural statistics of the environment. In two experiments, subjects were required to indicate what they saw in a large number of unique images, both with and without actual meaningful structure. The first experiment employed an open-ended response paradigm and used a variety of different images in noise; the second experiment only presented a series of faces embedded in noise, and required a forced-choice response from the subjects. The results in all conditions indicated that a high positive schizotypy score was associated with an increased tendency to perceive complex meaning in images comprised purely of random visual noise. Individuals high in positive schizotypy seemed to be employing a looser criterion (response bias) to determine what constituted a 'meaningful' image, while also being significantly less sensitive at the task than those low in positive schizotypy. Our results suggest that differences in perceptual performance for individuals high in positive schizotypy are not related to increased suggestibility or susceptibility to instruction, as had previously been suggested. Instead, the observed reductions in sensitivity along with increased response bias toward seeing something that is not there, indirectly implicated subtle neurophysiological differences associated with the personality dimension of schizotypy, that are theoretically pertinent to the continuum of schizophrenia and hallucination-proneness.

Encoding and estimation of first- and second-order binocular disparity in natural images

•

First- and second-order responses to natural binocular images are correlated.

•

Second-order mechanisms can improve the accuracy of disparity estimation.

•

Second-order mechanisms can extend the depth range of binocular stereopsis.

The first stage of processing of binocular information in the visual cortex is performed by mechanisms that are bandpass-tuned for spatial frequency and orientation. Psychophysical and physiological evidence have also demonstrated the existence of second-order mechanisms in binocular processing, which can encode disparities that are not directly accessible to first-order mechanisms. We compared the responses of first- and second-order binocular filters to natural images. We found that the responses of the second-order mechanisms are to some extent correlated with the responses of the first-order mechanisms, and that they can contribute to increasing both the accuracy, and depth range, of binocular stereopsis.

Objective Quality Assessment of Interpolated Natural Images

Image interpolation techniques that create high-resolution images from low-resolution (LR) images are widely used in real world applications, but how to evaluate the quality of interpolated images is not a well-resolved issue. Subjective assessment methods are useful and reliable, but are also slow and expensive. Here, we propose an objective method to assess the quality of an interpolated natural image using the available LR image as a reference. Our method adopts a natural scene statistics (NSS) framework, where image quality degradation is gauged by the deviation of its statistical features from the NSS models trained upon high-quality natural images. Two distortion measures are proposed, namely, interpolated natural image distortion (IND) and weighted IND. Validations by subjective tests show that the proposed approach performs statistically equivalent or sometimes better than an average human subject. Moreover, we demonstrate the potential application of the proposed method in parameter tuning of image interpolation algorithms.

A higher order visual neuron tuned to the spatial amplitude spectra of natural scenes

Animal sensory systems are optimally adapted to those features typically encountered in natural surrounds, thus allowing neurons with limited bandwidth to encode challengingly large input ranges. Natural scenes are not random, and peripheral visual systems in vertebrates and insects have evolved to respond efficiently to their typical spatial statistics. The mammalian visual cortex is also tuned to natural spatial statistics, but less is known about coding in higher order neurons in insects. To redress this we here record intracellularly from a higher order visual neuron in the hoverfly. We show that the cSIFE neuron, which is inhibited by stationary images, is maximally inhibited when the slope constant of the amplitude spectrum is close to the mean in natural scenes. The behavioural optomotor response is also strongest to images with naturalistic image statistics. Our results thus reveal a close coupling between the inherent statistics of natural scenes and higher order visual processing in insects.

Temporal Structure of Human Gaze Dynamics Is Invariant During Free Viewing

We investigate the dynamic structure of human gaze and present an experimental study of the frequency components of the change in gaze position over time during free viewing of computer-generated fractal images. We show that changes in gaze position are scale-invariant in time with statistical properties that are characteristic of a random walk process. We quantify and track changes in the temporal structure using a well-defined scaling parameter called the Hurst exponent, H. We find H is robust regardless of the spatial complexity generated by the fractal images. In addition, we find the Hurst exponent is invariant across all participants, including those with distinct changes to higher order visual processes due to neural degeneration. The value we find for H of 0.57 shows that the gaze dynamics during free viewing of fractal images are consistent with a random walk process with persistent movements. Our research suggests the human visual system may have a common strategy that drives the dynamics of human gaze during exploration.