A reconfigurable real-time morphological system for augmented vision

There is a significant number of visually impaired individuals who suffer sensitivity loss to high spatial frequencies, for whom current optical devices are limited in degree of visual aid and practical application. Digital image and video processing offers a variety of effective visual enhancement methods that can be utilised to obtain a practical augmented vision head-mounted display device. The high spatial frequencies of an image can be extracted by edge detection techniques and overlaid on top of the original image to improve visual perception among the visually impaired. Augmented visual aid devices require highly user-customisable algorithm designs for subjective configuration per task, where current digital image processing visual aids offer very little user-configurable options. This paper presents a highly user-reconfigurable morphological edge enhancement system on field-programmable gate array, where the morphological, internal and external edge gradients can be selected from the presented architecture with specified edge thickness and magnitude. In addition, the morphology architecture supports reconfigurable shape structuring elements and configurable morphological operations. The proposed morphology-based visual enhancement system introduces a high degree of user flexibility in addition to meeting real-time constraints capable of obtaining 93 fps for high-definition image resolution

Role of lateral and feedback connections in primary visual cortex in the processing of spatiotemporal regularity: a TMS study

Our human visual system exploits spatiotemporal regularity to interpret incoming visual signals. With a dynamic stimulus sequence of four collinear bars (predictors) appearing consecutively toward the fovea, followed by a target bar with varying contrasts, we have previously found that this predictable spatiotemporal stimulus structure enhances target detection performance and its underlying neural process starts in the primary visual cortex (area V1). However, the relative contribution of V1 lateral and feedback connections in the processing of spatiotemporal regularity remains unclear. In this study we measured human contrast detection of a briefly presented foveal target that was embedded in a dynamic collinear predictor-target sequence. Transcranial magnetic stimulation (TMS) was used to selectively disrupt V1 horizontal and feedback connections in the processing of predictors. The coil was positioned over a cortical location corresponding to the location of the last predictor prior to target onset. Single-pulse TMS at an intensity of 10% below phosphene threshold was delivered at 20 or 90ms after the predictor onset. Our analysis revealed that the delivery of TMS at both time windows equally reduced, but did not abolish, the facilitation effect of the predictors on target detection. Furthermore, if the predictors’ ordination was randomized to suppress V1 lateral connections, the TMS disruption was significantly more evident at 20ms than at 90ms time window. We suggest that both lateral and feedback connections contribute to the encoding of spatiotemporal regularity in V1. These findings develop understanding of how our visual system exploits spatiotemporal regularity to facilitate the efficiency of visual perception

Is there a general trait of susceptibility to simultaneous contrast?

Individuals differ in their susceptibility to simultaneous contrast. Are the underlying differences in neural machinery conserved across different stimulus dimensions? We measured the extent to which 101 subjects perceived simultaneous contrast on the dimensions of luminance, colour, luminance contrast, colour contrast, orientation, spatial frequency, motion and numerosity. Individual differences showed re-test reliability for each dimension (0.32ICC(c,1)0.78, p0.05), but susceptibility to simultaneous contrast, with a few exceptions, was not correlated across dimensions. Either susceptibility to contrast arises empirically from an individual's interactions with the environment, or it is genetically determined but independently for different dimensions

Image enhancement using fuzzy intensity measure and adaptive clipping histogram equalization

Image enhancement aims at processing an input image so that the visual content of the output image is more pleasing or more useful for certain applications. Although histogram equalization is widely used in image enhancement due to its simplicity and effectiveness, it changes the mean brightness of the enhanced image and introduces a high level of noise and distortion. To address these problems, this paper proposes image enhancement using fuzzy intensity measure and adaptive clipping histogram equalization (FIMHE). FIMHE uses fuzzy intensity measure to first segment the histogram of the original image, and then clip the histogram adaptively in order to prevent excessive image enhancement. Experiments on the Berkeley database and CVF-UGR-Image database show that FIMHE outperforms state-of-the-art histogram equalization based methods

Context-Sensitive Binding by the Laminar Circuits of V1 and V2: A Unified Model of Perceptual Grouping, Attention, and Orientation Contrast

A detailed neural model is presented of how the laminar circuits of visual cortical areas V1 and V2 implement context-sensitive binding processes such as perceptual grouping and attention. The model proposes how specific laminar circuits allow the responses of visual cortical neurons to be determined not only by the stimuli within their classical receptive fields, but also to be strongly influenced by stimuli in the extra-classical surround. This context-sensitive visual processing can greatly enhance the analysis of visual scenes, especially those containing targets that are low contrast, partially occluded, or crowded by distractors. We show how interactions of feedforward, feedback and horizontal circuitry can implement several types of contextual processing simultaneously, using shared laminar circuits. In particular, we present computer simulations which suggest how top-down attention and preattentive perceptual grouping, two processes that are fundamental for visual binding, can interact, with attentional enhancement selectively propagating along groupings of both real and illusory contours, thereby showing how attention can selectively enhance object representations. These simulations also illustrate how attention may have a stronger facilitatory effect on low contrast than on high contrast stimuli, and how pop-out from orientation contrast may occur. The specific functional roles which the model proposes for the cortical layers allow several testable neurophysiological predictions to be made. The results presented here simulate only the boundary grouping system of adult cortical architecture. However we also discuss how this model contributes to a larger neural theory of vision which suggests how intracortical and intercortical feedback help to stabilize development and learning within these cortical circuits. Although feedback plays a key role, fast feedforward processing is possible in response to unambiguous information. Model circuits are capable of synchronizing quickly, but context-sensitive persistence of previous events can influence how synchrony develops. Although these results focus on how the interblob cortical processing stream controls boundary grouping and attention, related modeling of the blob cortical processing stream suggests how visible surfaces are formed, and modeling of the motion stream suggests how transient responses to scenic changes can control long-range apparent motion and also attract spatial attention.Defense Advanced Research Projects agency and the Office of Naval Research (N00014-95-1-0409); National Science Foundation (IRI 94-01659, IRI 97-20333); ONR (N00014-92-J-1309, N00014-95-1-0657