Processing of Synthetic Aperture Radar Images by a Multiscale Boundary Contour System and Feature Contour System

An improved Boundary Contour System (BCS) and Feature Contour System (FCS) neural network model of preattentive vision is applied to large images containing range data gathered by a synthetic aperture radar (SAR) sensor. The goal of processing is to make structures such as motor vehicles, roads, or buildings more salient and more interpretable to human observers than they are in the original imagery. Early processing by shunting center-surround networks compresses signal dynamic range and performs local contrast enhancement. Subsequent processing by filters sensitive to oriented contrast, including short-range competition and long-range cooperation, segments the image into regions. The segmentation is performed by three "copies" of the BCS and FCS, of small, medium, and large scales, wherein the "short-range" and "long-range" interactions within each scale occur over smaller or larger distances, corresponding to the size of the early filters of each scale. A diffusive filling-in operation within the segmented regions at each scale produces coherent surface representations. The combination of BCS and FCS helps to locate and enhance structure over regions of many pixels, without the resulting blur characteristic of approaches based on low spatial frequency filtering alone.

Cortical Dynamics of Visual Motion Perception: Short-Range and Long Range Apparent Motion

This article describes further evidence for a new neural network theory of biological motion perception that is called a Motion Boundary Contour System. This theory clarifies why parallel streams Vl-> V2 and Vl-> MT exist for static form and motion form processing among the areas Vl, V2, and MT of visual cortex. The Motion Boundary Contour System consists of several parallel copies, such that each copy is activated by a different range of receptive field sizes. Each copy is further subdivided into two hierarchically organized subsystems: a Motion Oriented Contrast Filter, or MOC Filter, for preprocessing moving images; and a Cooperative-Competitive Feedback Loop, or CC Loop, for generating emergent boundary segmentations of the filtered signals. The present article uses the MOC Filter to explain a variety of classical and recent data about short-range and long-range apparent motion percepts that have not yet been explained by alternative models. These data include split motion; reverse-contrast gamma motion; delta motion; visual inertia; group motion in response to a reverse-contrast Ternus display at short interstimulus intervals; speed-up of motion velocity as interfiash distance increases or flash duration decreases; dependence of the transition from element motion to group motion on stimulus duration and size; various classical dependencies between flash duration, spatial separation, interstimulus interval, and motion threshold known as Korte's Laws; and dependence of motion strength on stimulus orientation and spatial frequency. These results supplement earlier explanations by the model of apparent motion data that other models have not explained; a recent proposed solution of the global aperture problem, including explanations of motion capture and induced motion; an explanation of how parallel cortical systems for static form perception and motion form perception may develop, including a demonstration that these parallel systems are variations on a common cortical design; an explanation of why the geometries of static form and motion form differ, in particular why opposite orientations differ by 90°, whereas opposite directions differ by 180°, and why a cortical stream Vl -> V2 -> MT is needed; and a summary of how the main properties of other motion perception models can be assimilated into different parts of the Motion Boundary Contour System design.

Cortical Dynamics of Visual Motion Perception: Short-Range and Long-Range Apparent Motion

This article describes further evidence for a new neural network theory of biological motion perception. The theory clarifies why parallel streams Vl --> V2, Vl --> MT, and Vl --> V2 --> MT exist for static form and motion form processing among the areas Vl, V2, and MT of visual cortex. The theory suggests that the static form system (Static BCS) generates emergent boundary segmentations whose outputs are insensitive to direction-ofcontrast and insensitive to direction-of-motion, whereas the motion form system (Motion BCS) generates emergent boundary segmentations whose outputs are insensitive to directionof-contrast but sensitive to direction-of-motion. The theory is used to explain classical and recent data about short-range and long-range apparent motion percepts that have not yet been explained by alternative models. These data include beta motion; split motion; gamma motion and reverse-contrast gamma motion; delta motion; visual inertia; the transition from group motion to element motion in response to a Ternus display as the interstimulus interval (ISI) decreases; group motion in response to a reverse-contrast Ternus display even at short ISIs; speed-up of motion velocity as interflash distance increases or flash duration decreases; dependence of the transition from element motion to group motion on stimulus duration and size; various classical dependencies between flash duration, spatial separation, ISI, and motion threshold known as Korte's Laws; dependence of motion strength on stimulus orientation and spatial frequency; short-range and long-range form-color interactions; and binocular interactions of flashes to different eyes.

Processing of Synthetic Aperture Radar Images by the Boundary Contour System and Feature Contour System

An improved Boundary Contour System (BCS) and Feature Contour System (FCS) neural network model of preattentive vision is applied to two large images containing range data gathered by a synthetic aperture radar (SAR) sensor. The goal of processing is to make structures such as motor vehicles, roads, or buildings more salient and more interpretable to human observers than they are in the original imagery. Early processing by shunting center-surround networks compresses signal dynamic range and performs local contrast enhancement. Subsequent processing by filters sensitive to oriented contrast, including short-range competition and long-range cooperation, segments the image into regions. Finally, a diffusive filling-in operation within the segmented regions produces coherent visible structures. The combination of BCS and FCS helps to locate and enhance structure over regions of many pixels, without the resulting blur characteristic of approaches based on low spatial frequency filtering alone.

3-D Vision and Figure-Ground Separation by Visual Cortex

A neural network theory of :3-D vision, called FACADE Theory, is described. The theory proposes a solution of the classical figure-ground problem for biological vision. It does so by suggesting how boundary representations and surface representations are formed within a Boundary Contour System (BCS) and a Feature Contour System (FCS). The BCS and FCS interact reciprocally to form 3-D boundary and surface representations that arc mutually consistent. Their interactions generate 3-D percepts wherein occluding and occluded object completed, and grouped. The theory clarifies how preattentive processes of 3-D perception and figure-ground separation interact reciprocally with attentive processes of spatial localization, object recognition, and visual search. A new theory of stereopsis is proposed that predicts how cells sensitive to multiple spatial frequencies, disparities, and orientations are combined by context-sensitive filtering, competition, and cooperation to form coherent BCS boundary segmentations. Several factors contribute to figure-ground pop-out, including: boundary contrast between spatially contiguous boundaries, whether due to scenic differences in luminance, color, spatial frequency, or disparity; partially ordered interactions from larger spatial scales and disparities to smaller scales and disparities; and surface filling-in restricted to regions surrounded by a connected boundary. Phenomena such as 3-D pop-out from a 2-D picture, DaVinci stereopsis, a 3-D neon color spreading, completion of partially occluded objects, and figure-ground reversals are analysed. The BCS and FCS sub-systems model aspects of how the two parvocellular cortical processing streams that join the Lateral Geniculate Nucleus to prestriate cortical area V4 interact to generate a multiplexed representation of Form-And-Color-And-Depth, or FACADE, within area V4. Area V4 is suggested to support figure-ground separation and to interact. with cortical mechanisms of spatial attention, attentive objcect learning, and visual search. Adaptive Resonance Theory (ART) mechanisms model aspects of how prestriate visual cortex interacts reciprocally with a visual object recognition system in inferotemporal cortex (IT) for purposes of attentive object learning and categorization. Object attention mechanisms of the What cortical processing stream through IT cortex are distinguished from spatial attention mechanisms of the Where cortical processing stream through parietal cortex. Parvocellular BCS and FCS signals interact with the model What stream. Parvocellular FCS and magnocellular Motion BCS signals interact with the model Where stream. Reciprocal interactions between these visual, What, and Where mechanisms arc used to discuss data about visual search and saccadic eye movements, including fast search of conjunctive targets, search of 3-D surfaces, selective search of like-colored targets, attentive tracking of multi-element groupings, and recursive search of simultaneously presented targets.

A Solution of the Figure-ground Problem for Biological Vision

A neural network model of 3-D visual perception and figure-ground separation by visual cortex is introduced. The theory provides a unified explanation of how a 2-D image may generate a 3-D percept; how figures pop-out from cluttered backgrounds; how spatially sparse disparity cues can generate continuous surface representations at different perceived depths; how representations of occluded regions can be completed and recognized without usually being seen; how occluded regions can sometimes be seen during percepts of transparency; how high spatial frequency parts of an image may appear closer than low spatial frequency parts; how sharp targets are detected better against a figure and blurred targets are detector better against a background; how low spatial frequency parts of an image may be fused while high spatial frequency parts are rivalrous; how sparse blue cones can generate vivid blue surface percepts; how 3-D neon color spreading, visual phantoms, and tissue contrast percepts are generated; how conjunctions of color-and-depth may rapidly pop-out during visual search. These explanations arise derived from an ecological analysis of how monocularly viewed parts of an image inherit the appropriate depth from contiguous binocularly viewed parts, as during DaVinci stereopsis. The model predicts the functional role and ordering of multiple interactions within and between the two parvocellular processing streams that join LGN to prestriate area V4. Interactions from cells representing larger scales and disparities to cells representing smaller scales and disparities are of particular importance.

Self-organized vegetation patterning as a fingerprint of climate and human impact on semi-arid ecosystems

Spatially periodic vegetation patterns are well known in arid and semi-arid regions around the world. Mathematical models have been developed that attribute this phenomenon to a symmetry-breaking instability. Such models are based on the interplay between competitive and facilitative influences that the vegetation exerts on its own dynamics when it is constrained by arid conditions, but evidence for these predictions is still lacking. Moreover, not all models can account for the development of regularly spaced spots of bare ground in the absence of a soil prepattern. We applied Fourier analysis to high-resolution, remotely sensed data taken at either end of a 40-year interval in southern Niger. Statistical comparisons based on this textural characterization gave us broad-scale evidence that the decrease in rainfall over recent decades in the sub-Saharan Sahel has been accompanied by a detectable shift from homogeneous vegetation cover to spotted patterns marked by a spatial frequency of about 20 cycles km-1. Wood cutting and grazing by domestic animals have led to a much more marked transition in unprotected areas than in a protected reserve. Field measurements demonstrated that the dominant spatial frequency was endogenous rather than reflecting the spatial variation of any pre-existing heterogeneity in soil properties. All these results support the use of models that can account for periodic vegetation patterns without invoking substrate heterogeneity or anisotropy, and provide new elements for further developments, refinements and tests. This study underlines the potential of studying vegetation pattern properties for monitoring climatic and human impacts on the extensive fragile areas bordering hot deserts. Explicit consideration of vegetation self-patterning may also improve our understanding of vegetation and climate interactions in arid areas. © 2006 The Authors.

Surface plasmon resonance in nanostructured metal films under the Kretschmann configuration

We systematically investigated the surface plasmon resonance in one-dimensional (1D) subwavelength nanostructured metal films under the Kretschmann configuration. We calculated the reflectance, transmittance, and absorption for varying the dielectric fill factor, the period of the 1D nanostructure, and the metal film thickness. We have found that the small dielectric slits in the metal films reduce the surface plasmon resonance angle and move it toward the critical angle for total internal reflection. The reduction in surface plasmon resonance angle in nanostructured metal films is due to the increased intrinsic free electron oscillation frequency in metal nanostructures. Also we have found that the increasing the spatial frequency of the 1D nanograting reduces the surface plasmon resonance angle, which indicates that less momentum is needed to match the momentum of the surface plasmon-polariton. The variation in the nanostructured metal film thickness changes the resonance angle slightly, but mainly remains as a mean to adjust the coupling between the incident optical wave and the surface plasmon-polariton wave. © 2009 American Institute of Physics.

How does the short-wavelength-sensitive contrast sensitivity function for detection and resolution change with age in the periphery?

To determine the age-related change in the peripheral short-wavelength-sensitive (SWS) grating contrast sensitivity function (CSF), cut-off spatial frequency (acuity) and contrast sensitivity for both a detection and resolution task were measured at 8 degrees eccentricity under conditions of SWS-cone isolation for 51 subjects (19-72 years). The acuity for both the detection and resolution task declined with age, the detection acuity being significantly higher than the resolution acuity at all ages (p

Do different 'magnocellular tasks' probe the same neural substrate?

The sensory abnormalities associated with disorders such as dyslexia, autism and schizophrenia have often been attributed to a generalized deficit in the visual magnocellular-dorsal stream and its auditory homologue. To probe magnocellular function, various psychophysical tasks are often employed that require the processing of rapidly changing stimuli. But is performance on these several tasks supported by a common substrate? To answer this question, we tested a cohort of 1060 individuals on four 'magnocellular tasks': detection of low-spatial-frequency gratings reversing in contrast at a high temporal frequency (so-called frequency-doubled gratings); detection of pulsed low-spatial-frequency gratings on a steady luminance pedestal; detection of coherent motion; and auditory discrimination of temporal order. Although all tasks showed test-retest reliability, only one pair shared more than 4 per cent of variance. Correlations within the set of 'magnocellular tasks' were similar to the correlations between those tasks and a 'non-magnocellular task', and there was little consistency between 'magnocellular deficit' groups comprising individuals with the lowest sensitivity for each task. Our results suggest that different 'magnocellular tasks' reflect different sources of variance, and thus are not general measures of 'magnocellular function'.

An Investigation Into Features For Multi-View Lipreading

For the first time in this paper we present results showing the effect of speaker head pose angle on automatic lip-reading performance over a wide range of closely spaced angles. We analyse the effect head pose has upon the features themselves and show that by selecting coefficients with minimum variance w.r.t. pose angle, recognition performance can be improved when train-test pose angles differ. Experiments are conducted using the initial phase of a unique multi view Audio-Visual database designed specifically for research and development of pose-invariant lip-reading systems. We firstly show that it is the higher order horizontal spatial frequency components that become most detrimental as the pose deviates. Secondly we assess the performance of different feature selection masks across a range of pose angles including a new mask based on Minimum Cross-Pose Variance coefficients. We report a relative improvement of 50% in Word Error Rate when using our selection mask over a common energy based selection during profile view lip-reading.

Variants in the 1q21 risk region are associated with a visual endophenotype of autism and schizophrenia

Deficits in sensitivity to visual stimuli of low spatial frequency and high temporal frequency (so-called frequency-doubled gratings) have been demonstrated both in schizophrenia and in autism spectrum disorder (ASD). Such basic perceptual functions are ideal candidates for molecular genetic study, because the underlying neural mechanisms are well characterized; but they have sometimes been overlooked in favor of cognitive and neurophysiological endophenotypes, for which neural substrates are often unknown. Here, we report a genome-wide association study of a basic visual endophenotype associated with psychological disorder. Sensitivity to frequency-doubled gratings was measured in 1060 healthy young adults, and analyzed for association with genotype using linear regression at 642758 single nucleotide polymorphism (SNP) markers. A significant association (P=7.9×10) was found with the SNP marker rs1797052, situated in the 5′-untranslated region of PDZK1; each additional copy of the minor allele was associated with an increase in sensitivity equivalent to more than half a standard deviation. A permutation procedure, which accounts for multiple testing, showed that the association was significant at the α=0.005 level. The region on chromosome 1q21.1 surrounding PDZK1 is an established susceptibility locus both for schizophrenia and for ASD, mirroring the common association of the visual endophenotype with the two disorders. PDZK1 interacts with N-methyl-d-aspartate receptors and neuroligins, which have been implicated in the etiologies of schizophrenia and ASD. These findings suggest that perceptual abnormalities observed in two different disorders may be linked by common genetic elements. © 2013 John Wiley & Sons Ltd and International Behavioural and Neural Genetics Society.

Hyperbolic Polaritonic Crystals Based on Nanostructured Nanorod Metamaterials

Surface plasmon polaritons usually exist on a few suitable plasmonic materials; however, nanostructured plasmonic metamaterials allow a much broader range of optical properties to be designed. Here, bottom-up and top-down nanostructuring are combined, creating hyperbolic metamaterial-based photonic crystals termed hyperbolic polaritonic crystals, allowing free-space access to the high spatial frequency modes supported by these metamaterials.

Disparity energy model with keypoint disparity validation

A biological disparity energy model can estimate local depth information by using a population of V1 complex cells. Instead of applying an analytical model which explicitly involves cell parameters like spatial frequency, orientation, binocular phase and position difference, we developed a model which only involves the cells’ responses, such that disparity can be extracted from a population code, using only a set of previously trained cells with random-dot stereograms of uniform disparity. Despite good results in smooth regions, the model needs complementary processing, notably at depth transitions. We therefore introduce a new model to extract disparity at keypoints such as edge junctions, line endings and points with large curvature. Responses of end-stopped cells serve to detect keypoints, and those of simple cells are used to detect orientations of their underlying line and edge structures. Annotated keypoints are then used in the leftright matching process, with a hierarchical, multi-scale tree structure and a saliency map to segregate disparity. By combining both models we can (re)define depth transitions and regions where the disparity energy model is less accurate.

Image quality optimization, via application of contextual contrast sensitivity and discrimination functions

What is the best luminance contrast weighting-function for image quality optimization? Traditionally measured contrast sensitivity functions (CSFs), have been often used as weighting-functions in image quality and difference metrics. Such weightings have been shown to result in increased sharpness and perceived quality of test images. We suggest contextual CSFs (cCSFs) and contextual discrimination functions (cVPFs) should provide bases for further improvement, since these are directly measured from pictorial scenes, modeling threshold and suprathreshold sensitivities within the context of complex masking information. Image quality assessment is understood to require detection and discrimination of masked signals, making contextual sensitivity and discrimination functions directly relevant. In this investigation, test images are weighted with a traditional CSF, cCSF, cVPF and a constant function. Controlled mutations of these functions are also applied as weighting-functions, seeking the optimal spatial frequency band weighting for quality optimization. Image quality, sharpness and naturalness are then assessed in two-alternative forced-choice psychophysical tests. We show that maximal quality for our test images, results from cCSFs and cVPFs, mutated to boost contrast in the higher visible frequencies.