Bruce C. Hansen

A horizontal bias in human visual processing of orientation and its correspondence to the structural components of natural scenes.

Many encoding mechanisms and processing strategies in the visual system appear to have evolved to better process the prevalent content in the visual world. Here we examine the relationship between the prevalence of natural scene content at different orientations and visual ability for detecting oriented natural scene content. Whereas testing with isolated gratings shows best performance at horizontal and vertical (the oblique effect), we report that when tested with natural scene content, performance is best at obliques and worst at horizontal (the horizontal effect). The present analysis of typical natural scenes shows that the prevalence of natural scene content matches the inverse of this horizontal effect pattern with most scene content at horizontal, next most at vertical, and least at obliques. We suggest that encoding of orientation may have evolved to accommodate the anisotropy in natural scene content by perceptually discounting the most prevalent oriented content in a scene, thereby increasing the relative salience of objects and other content in a scene when viewed against a typical natural background.

Peripheral vision: Good for biological motion, bad for signal noise segregation?

Biological motion perception, having both evolutionary and social importance, is performed by the human visual system with a high degree of sensitivity. It is unclear whether peripheral vision has access to the specialized neural systems underlying biological motion perception; however, given the motion component, one would expect peripheral vision to be, if not specialized, at least highly accurate in perceiving biological motion. Here we show that the periphery can indeed perceive biological motion. However, the periphery suffers from an inability to detect biological motion signals when they are embedded in dynamic visual noise. We suggest that this peripheral deficit is not due to biological motion perception per se, but to signal/noise segregation.

An advanced image fusion algorithm based on wavelet transform: incorporation with PCA and morphological processing

There are numerous applications for image fusion, some of which include medical imaging, remote sensing, nighttime operations and multi-spectral imaging. In general, the discrete wavelet transform (DWT) and various pyramids (such as Laplacian, ratio, contrast, gradient and morphological pyramids) are the most common and effective methods. For quantitative evaluation of the quality of fused imagery, the root mean square error (RMSE) is the most suitable measure of quality if there is a “ground truth” image available; otherwise, the entropy, spatial frequency or image quality index of the input images and the fused images can be calculated and compared. Here, after analyzing the pyramids’ performance with the four measures mentioned, an advanced wavelet transform (aDWT) method that incorporates principal component analysis (PCA) and morphological processing into a regular DWT fusion algorithm is presented. Specifically, at each scale of the wavelet transformed images, a principle vector was derived from two input images and then applied to two of the images’ approximation coefficients (i.e., they were fused by using the principal eigenvector). For the detail coefficients (i.e., three quarters of the coefficients), the larger absolute values were chosen and subjected to a neighborhood morphological processing procedure which served to verify the selected pixels by using a “filling” and “cleaning” operation (this operation filled or removed isolated pixels in a 3-by-3 local region). The fusion performance of the advanced DWT (aDWT) method proposed here was compared with six other common methods, and, based on the four quantitative measures, was found to perform the best when tested on the four input image types. Since the different image sources used here varied with respect to intensity, contrast, noise, and intrinsic characteristics, the aDWT is a promising image fusion procedure for inhomogeneous imagery.

Perceptual anisotropies in visual processing and their relation to natural image statistics

The amplitude spectra of natural scenes are typically biased in terms of the amount of content at the cardinal orientations relative to the oblique orientations. This anisotropic distribution has been related to the ‘oblique effect’ (the greater visual sensitivity for simple line/grating stimuli at cardinal compared to oblique orientations). However, we have recently shown that with complex visual stimuli possessing broadband spatial content (i.e. random phase noise patterns), sensitivity for detecting oriented manipulations of amplitude is best for oblique orientations, and worst for horizontal orientations (the ‘horizontal effect’). Here we investigated this effect with respect to the phase spectra of natural scenes. Oriented manipulations of both amplitude and phase were made on a set of natural scene images that were dominated by naturally occurring structure at one of four orientations in order to determine whether the presence of predominant scene content, carried by the Fourier phase spectra, altered the ability to detect an oriented increment of amplitude. The horizontal effect was observed regardless of any scenes content bias. In addition, a content-dependent effect was observed which could be related to the presence of spatial structure conveyed by the phase spectra of this set of natural scenes. Results are evaluated in the context of a divisive normalization model.

Anodal transcranial direct current stimulation reduces psychophysically measured surround suppression in the human visual cortex.

Transcranial direct current stimulation (tDCS) is a safe, non-invasive technique for transiently modulating the balance of excitation and inhibition within the human brain. It has been reported that anodal tDCS can reduce both GABA mediated inhibition and GABA concentration within the human motor cortex. As GABA mediated inhibition is thought to be a key modulator of plasticity within the adult brain, these findings have broad implications for the future use of tDCS. It is important, therefore, to establish whether tDCS can exert similar effects within non-motor brain areas. The aim of this study was to assess whether anodal tDCS could reduce inhibitory interactions within the human visual cortex. Psychophysical measures of surround suppression were used as an index of inhibition within V1. Overlay suppression, which is thought to originate within the lateral geniculate nucleus (LGN), was also measured as a control. Anodal stimulation of the occipital poles significantly reduced psychophysical surround suppression, but had no effect on overlay suppression. This effect was specific to anodal stimulation as cathodal stimulation had no effect on either measure. These psychophysical results provide the first evidence for tDCS-induced reductions of intracortical inhibition within the human visual cortex.

The Role of Higher Order Image Statistics in Masking Scene Gist Recognition

In the present article, we investigated whether higher order image statistics, which are known to be carried by the Fourier phase spectrum, are sufficient to affect scene gist recognition. In Experiment 1, we compared the scene gist masking strength of four masking image types that varied in their degrees of second- and higher order relationships: normal scene images, scene textures, phase-randomized scene images, and white noise. Masking effects were the largest for masking images that possessed significant higher order image statistics (scene images and scene textures) as compared with masking images that did not (phase-randomized scenes and white noise), with scene image masks yielding the largest masking effects. In a control study, we eliminated all differences in the second-order statistics of the masks, while maintaining differences in their higher order statistics by comparing masking by scene textures rather than by their phase-randomized versions, and showed that the former produced significantly stronger gist masking. Experiments 2 and 3 were designed to test whether conceptual masking could account for the differences in the strength of the scene texture and phase-randomized masks used in Experiment 1, and revealed that the recognizability of scene texture masks explained just 1% of their masking variance. Together, the results suggest that (1) masks containing the higher order statistical structure of scenes are more effective at masking scene gist processing than are masks lacking such structure, and (2) much of the disruption of scene gist recognition that one might be tempted to attribute to conceptual masking is due to spatial masking.

Influence of scale and orientation on the visual perception of natural scenes

It is well known that the distribution of spatial content with respect to spatial scale in real-world scenes falls in accordance with a 1/ f α relation. Equally well known is the tendency for an orientation bias in scene content with the predominant bias in content at the horizontal and vertical orientations. This has led to the suggestion of a relationship in which the mechanisms of the human visual system are optimized for processing such regularities. Here we review current literature concerning the measurement of these regularities (via Fourier analysis) of natural scenes in the context of other work that has psychophysically assessed the extent to which visual perception exploits such regularities of spatial content. In addition, 2 psychophysical experiments are presented that extend this literature and argue for the importance of these regularities in perceiving orientation in real-world visual stimuli.

Discrimination of amplitude spectrum slope in the fovea and parafovea and the local amplitude distributions of natural scene imagery.

A number of studies have investigated whether human visual performance can be related to the general form of the amplitude spectra (i.e., 1/f(alpha)) of natural scenes. Here, it is argued that there are some discrepancies in the data between some of those studies and that one possible explanation for the discrepancies may be related to differences in methodology (e.g., stimuli presented to the fovea as opposed to the parafovea). We sought to resolve some of the discrepancies with two psychophysical paradigms involving alpha discrimination with visual noise and natural scene image patches presented to the fovea or parafovea. Fovea-parafovea threshold differences were apparent for stimuli possessing alpha values < 1.0, with the parafovea typically showing highest thresholds for reference alpha values in the 0.74-0.85 range. Both fovea and parafovea thresholds were lowest in the 1.2-1.4 range. In addition, we conducted a local amplitude distribution analysis (i.e., assessed local alpha) with a large set of high-resolution natural scene imagery and found that the results of that analysis provided a better account of the alpha discrimination thresholds for stimuli presented to the fovea as opposed to the parafovea.

Different spatial frequency bands selectively signal for natural image statistics in the early visual system

Early visual evoked potentials (VEPs) measured in humans have recently been observed to be modulated by the image statistics of natural scene imagery. Specifically, the early VEP is dominated by a strong positivity when participants view minimally complex natural scene imagery, with the magnitude of that component being modulated by luminance contrast differences across spatial frequency (i.e., the slope of the amplitude spectrum). For scenes high in structural complexity, the early VEP is dominated by a prominent negativity that exhibits little dependency on luminance contrast. However, since natural scene imagery is broad band in terms of spatial frequency, it is not known whether the above-mentioned modulation results from a complex interaction within or between the early neural processes tuned to different bands of spatial frequency. Here, we sought to address this question by measuring early VEPs (specifically, the C1, P1, and N1 components) while human participants viewed natural scene imagery that was filtered to contain specific bands of spatial frequency information. The results show that the C1 component is largely unmodulated by the luminance statistics of natural scene imagery (being only measurable when such stimuli were made to contain high spatial frequencies). The P1 and N1, on the other hand, were observed to exhibit strong spatial frequency-dependent modulation to the luminance statistics of natural scene imagery. The results therefore suggest that the dependency of early VEPs on natural image statistics results from an interaction between the early neural processes tuned to different bands of spatial frequency.

From spatial frequency contrast to edge preponderance: the differential modulation of early visual evoked potentials by natural scene stimuli

The contrast response function of early visual evoked potentials elicited by sinusoidal gratings is known to exhibit characteristic potentials closely associated with the processes of parvocellular and magnocellular pathways. Specifically, the N1 component has been linked with parvocellular processes, while the P1 component has been linked with magnocellular processes. However, little is known regarding the response properties of the N1 and P1 components during the processing and encoding of complex (i.e., broadband) stimuli such as natural scenes. Here, we examine how established physical characteristics of natural scene imagery modulate the N1 and P1 components in humans by providing a systematic investigation of component modulation as visual stimuli are gradually built up from simple sinusoidal gratings to highly complex natural scene imagery. The results suggest that the relative dominance in signal output of the N1 and P1 components is dependent on spatial frequency (SF) luminance contrast for simple stimuli up to natural scene imagery possessing few edges. However, such a dependency shifts to a dominant N1 signal for natural scenes possessing abundant edge content and operates independently of SF luminance contrast.