Visual adjustments to temporal blur

Abstract

After observers have adapted to an edge that is spatially blurred or sharpened, a focused edge appears too sharp or blurred, respectively. These adjustments to blur may play an important role in calibrating spatial sensitivity. We examined whether similar adjustments influence the perception of temporal edges, by measuring the appearance of a step change in the luminance of a uniform field after adapting to blurred or sharpened transitions. Stimuli were square-wave alternations (at 1 to 8 Hz) filtered by changing the slope of the amplitude spectrum. A two-alternative-forced-choice task was used to adjust the slope until it appeared as a step change, or until it matched the perceived transitions in a reference stimulus. Observers could accurately set the waveform to a square wave, but only at the slower alternation rates. However, these settings were strongly biased by prior adaptation to filtered stimuli, or when the stimuli were viewed within temporally filtered surrounds. Control experiments suggest that the latter induction effects result directly from the temporal blur and are not simply a consequence of brightness induction in the fields. These results suggest that adaptation and induction adjust visual coding so that images are focused not only in space but also in time.

Visual discomfort and flicker

“…These slope changes have been studied extensively to examine how well visual coding might be matched to 1/ f spectra (e.g., Hanson and Hess, 2006; Johnson et al, 2011; Knill, Field, and Kersten, 1990; Tadmor and Tolhurst, 1994), and as a stimulus for probing blur perception and adaptation (Elliott, Georgeson, and Webster, 2011; Webster, Georgeson, and Webster, 2002; Webster and Marcos, 2017). Specifically, steeper slopes typically appear blurred, while shallower slopes appear too sharp, and these percepts occur both within the spatial and temporal domains (Bilson, Mizokami, & Webster, 2005). Juricevic et al (2010) previously showed that spatial images (Mondrians or filtered noise) were rated most comfortable when their amplitude spectrum was 1/ f , with discomfort increasing for both blurred and sharpened slopes.…”

Adaptation and visual coding

“…For example, natural images have more energy at low spatial and temporal frequencies (Field, 1987; Field & Brady, 1997; Tolhurst, Tadmor, & Chao, 1992; Van Hateren, 1993). Adaptation to this structure selectively reduces sensitivity to low spatial frequencies, resulting in marked changes in the shape of the contrast sensitivity function (CSF; Bex, Solomon, & Dakin, 2009; Webster & Miyahara, 1997) or in the tuning functions of individual cortical cells (Sharpee et al, 2006), though notably, the same adaptation does not bias the suprathreshold perception of image focus in space or time (Bilson, Mizokami, & Webster, 2005; Webster, Georgeson, & Webster, 2002)). Similar structure is found for the spatial variations in the chromatic contrast of scenes (Parraga, Troscianko, & Tolhurst, 2002), and adaptation to this chromatic structure can cause the normally low-pass chromatic CSF to become nearly band pass (Webster, Mizokami, Svec, & Elliott, 2006).…”

Adapting to blur produced by ocular high-order aberrations

“…Therefore, the subjective neutral point for image focus is shifted toward the sharpness or blur level of the adapting images. These aftereffects may reflect natural variants of the spatially selective adjustments studied extensively in the context of spatial frequency adaptation (Blakemore & Campbell, 1969; Blakemore & Sutton, 1969) and occur and can be selective for different types of images, for luminance or chromatic blur, spatial or temporal blur, and to different simulated depth planes (Battaglia, Jacobs, & Aslin, 2003; Bilson, Mizokami, & Webster, 2005; Webster et al, 2002; Webster, Mizokami, Svec, & Elliott, 2006), and thus, visual coding can readily adapt to many aspects of image blur.…”