An adaptive scale Gaussian filter to explain White’s illusion from the viewpoint of lightness assimilation for a large range of variation in spatial frequency of the grating and aspect ratio of the targets

Abstract

The variation between the actual and perceived lightness of a stimulus has strong dependency on its background, a phenomena commonly known as lightness induction in the literature of visual neuroscience and psychology. For instance, a gray patch may perceptually appear to be darker in a background while it looks brighter when the background is reversed. In the literature it is further reported that such variation can take place in two possible ways. In case of stimulus like the Simultaneous Brightness Contrast (SBC), the apparent lightness changes in the direction opposite to that of the background lightness, a phenomenon often referred to as lightness contrast, while in the others like neon colour spreading or checkerboard illusion it occurs opposite to that, and known as lightness assimilation. The White’s illusion is a typical one which according to many, does not completely conform to any of these two processes. This paper presents the result of quantification of the perceptual strength of the White’s illusion as a function of the width of the background square grating as well as the length of the gray patch. A linear filter model is further proposed to simulate the possible neurophysiological phenomena responsible for this particular visual experience. The model assumes that for the White’s illusion, where the edges are strong and quite a few, i.e., the spectrum is rich in high frequency components, the inhibitory surround in the classical Difference-of-Gaussians (DoG) filter gets suppressed, and the filter essentially reduces to an adaptive scale Gaussian kernel that brings about lightness assimilation. The linear filter model with a Gaussian kernel is used to simulate the White’s illusion phenomena with wide variation of spatial frequency of the background grating as well as the length of the gray patch. The appropriateness of the model is presented through simulation results, which are highly tuned to the present as well as earlier psychometric results.

Lightness induction enhancements and limitations at low frequency modulations across a variety of stimulus contexts

“…Considering just the MW stimuli, despite the smaller area of the flanker modulator compared to the assimilator, the flanker modulator still generated a surprisingly strong lightness induction effect, which suggests that if one were to control for modulator area, then the flanker effect may have been even stronger. Relatedly, it has been reported that the lightness induction of the MW stimulus does not depend on the aspect ratio of the target region, and hence the overall aspect ratio of the stimulus (Blakeslee & McCourt, 2004;Blakeslee, Padmanabhan & McCourt, 2016;Güçlü & Farell, 2005), but conflicting reports do exist (Mitra et al, 2018). Although, the magnitude of the MW stimulus has been shown to be resilient across a wide range of lower spatial frequencies, and demonstrates an increase across higher spatial frequencies (Blakeslee & McCourt, 2004;Helson & Rohles, 1959;White, 1979).…”

Regression Approach in the Evaluation of White’s Effect Magnitude in Comparison to Lightness

“…Blakeslee and McCourt [10][11][12][13] attempted to interpret effects like White's and others, for example simultaneous brightness contrast and grating induction using multiscale spatial filtering). They also determined that the effect also appears in the early stage of cortical filtering operations in the human visual system.…”