A probabilistic explanation of brightness scaling

Nundy, Surajit; Purves, Dale

doi:10.1073/pnas.172520399

Cited by 47 publications

(23 citation statements)

References 30 publications

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“…To understand how responses in V1 and V2͞V3 were related to perceived brightness, we conducted a third, exclusively psychophysical, experiment. Typically, the relationship between perceived brightness and surface luminance can be approximated by a power function, but the exponent of the function can vary strongly and depends critically on stimulus parameters (20). We therefore used exactly the same stimuli as in experiment 2 together with a magnitude estimation procedure.…”

Section: Control Experimentsmentioning

confidence: 99%

Responses of human visual cortex to uniform surfaces

Haynes

Lotto

Rees

2004

Proc. Natl. Acad. Sci. U.S.A.

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Surface perception is fundamental to human vision, yet most studies of visual cortex have focused on the processing of borders. We therefore investigated the responses of human visual cortex to parametric changes in the luminance of uniform surfaces by using functional MRI. Early visual areas V1 and V2͞V3 showed strong and reliable increases in signal for both increments and decrements in surface luminance. Responses were significantly larger for decrements than for increments, which was fully accounted for by differences in retinal illumination arising from asymmetric pupil dynamics. Responses to both sustained and transient changes of illumination were transient. Signals in early visual cortex scaled linearly with the magnitude of change in retinal illumination, as did subjects' subjective ratings of the perceived brightness of the stimuli. Our findings show that early visual cortex responds strongly to surfaces and that perception of surface brightness is compatible with brain responses at the earliest cortical stages of processing.T he perception of surfaces is fundamental to visual behavior, yet little is known about how they are processed in visual cortex. Early studies suggested that neurons in visual cortex respond strongly to edges but only weakly or not at all to uniform illumination (1). Subsequent work has therefore focused almost exclusively on neural mechanisms of contour processing. Indeed, in most contemporary computational models, visual cortical cells are characterized as filters that are unresponsive to uniform illumination (2, 3). The presence of strong edge responses and weak surface responses in early visual cortex is contrary to the intuition that perception of surface brightness should be mediated by neurons responding strongly to the entire spatial extent of a surface. Theoretical accounts of surface perception have therefore often postulated a processing of ''filling in'' that mediates creation of surface representations at some level in the visual system (4, 5). However, more recent reports suggest that some cells in primary visual cortex do indeed respond to the luminance of uniform surfaces (6-10). Furthermore, in humans there is a close relationship between perceived brightness contrast and responses in primary visual cortex (11)(12)(13)(14)(15), suggesting that other sensations of brightness may also be encoded in primary visual cortex. However, the cortical response function for surfaces of uniform luminance in early visual areas, and its relationship to perceived brightness, has remained uninvestigated.We therefore sought to address this question by using functional MRI (fMRI) to characterize the relationship between parametric variations in surface luminance, cortical responses, and perceived brightness. Understanding such a relationship is a prerequisite for a complete understanding of the general mechanisms and principles that underlie perception of brightness.When studying responses to uniform surfaces, it is critical to avoid contamination by contour-related processes. With ...

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Section: Control Experimentsmentioning

confidence: 99%

Responses of human visual cortex to uniform surfaces

Haynes

Lotto

Rees

2004

Proc. Natl. Acad. Sci. U.S.A.

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“…Other anomalies apparent in Figure 14 are (a) that the shape of the scaling function is more or less opposite for increments and decrements (decrements of the target with respect to any given background being the portion of the functions to the left of the vertical line pertinent to each one of the three scaling functions shown), (b) that the relationship between luminance and brightness varies dramatically as a function of the background luminance, and (c) that the slope of the relationship is greatest when the luminance of the test target is similar to the luminance of the background. No generally accepted explanation for any of this phenomenology has been forthcoming, although several theories have been advanced (see discussion in Nundy & Purves, 2002).…”

Section: General Framework For Understanding the Relationship Of Lumimentioning

confidence: 99%

Perceiving the Intensity of Light.

Purves¹,

Williams²,

Nundy³

et al. 2004

Psychological Review

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The relationship between luminance (i.e., the photometric intensity of light) and its perception (i.e., sensations of lightness or brightness) has long been a puzzle. In addition to the mystery of why these perceptual qualities do not scale with luminance in any simple way, "illusions" such as simultaneous brightness contrast, Mach bands, Craik-O'Brien-Cornsweet edge effects, and the Chubb-Sperling-Solomon illusion have all generated much interest but no generally accepted explanation. The authors review evidence that the full range of this perceptual phenomenology can be rationalized in terms of an empirical theory of vision. The implication of these observations is that perceptions of lightness and brightness are generated according to the probability distributions of the possible sources of luminance values in stimuli that are inevitably ambiguous.A fundamental problem in vision (and perception generally) was recognized at the beginning of the 18th century by George Berkeley (1709Berkeley ( /1975, who pointed out that the sources underlying visual stimuli are unknowable in any direct sense. The light that falls on the eye from any region of a scene conflates the contributions of reflectance, illumination, and transmittance (as well as a host of subsidiary factors that affect these parameters). As a result, the physical provenance of light reaching the eye-and therefore the significance of the stimulus for visually guided behavior-is profoundly uncertain. This fundamental fact presents a biological quandary. Successful behavior in a complex and potentially hostile environment clearly depends on responding appropriately to the physical sources of visual stimuli rather than to the stimuli as such. If, however, the retinal images generated by light cannot uniquely define the underlying reality the observer must deal with, how then does the visual system produce behavior that is generally successful?The purpose of this review is thus to consider evidence, much of it derived from our own experiments over the last few years, about the way the uncertain relationship between the physical world and the perceptual world is resolved by the nervous system (see Purves & Lotto, 2003). The gist of this body of work is that what one sees at any moment appears to be fully determined by the probability distributions of the possible sources of the stimulus rather than the physical qualities of the stimulus (which are ambiguous) or the properties of the objects and conditions that generated the stimulus (which cannot be known directly). Although this framework has several important precedents (see below), it differs from most mainstream neurobiological thinking in recent decades and suggests other ways of conceptualizing the purposes served by the known physiology of visual system circuitry. The context here for exploring the merits of this conception of vision is sensations of lightness and brightness, which are arguably the most fundamental qualities of human visual experience. Luminance, Brightness, and LightnessLuminance is ...

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“…While photometry accounts for the wavelength dependence of the human eye, it does not model the perceived brightness of different photometric intensities by a standard human observer [49, p. 152] [50,55]. Relative human brightness perception versus relative luminance adapted from data presented in [50] higher intensities to avoid saturation of, and damage to, the retina thus leading to the non linear relationship seen in Figure 2.4 [50].…”

Section: Perception Of Intensitymentioning

confidence: 99%

“…Relative human brightness perception versus relative luminance adapted from data presented in [50] higher intensities to avoid saturation of, and damage to, the retina thus leading to the non linear relationship seen in Figure 2.4 [50]. It is important to note that since the muscles in the eye take time to react and adjust the iris, the perception of brightness is different for a flash of light compared a light source that appears constant.…”

Section: Perception Of Intensitymentioning

confidence: 99%

“…CFF and CCF are defined as the frequency, in hertz, at which a light stimulus, with fluctuating intensity or color, appears to be completely steady to the average human observer [58]. Both CFF and CCF threshold are dependent on the average luminous flux, SPD, modulation frequency and modulation format of the source as well as the current vision regime [50,58]. Considering an incandescent light source with on-off modulation, CFF threshold saturates at about 15 Hz for rod-mediated (Scotopic) vision, whereas cone mediated (Photopic) vision reaches about 60 Hz before saturating [58].…”

Section: Color Mixingmentioning

confidence: 99%

See 1 more Smart Citation

Design and Implementation of Color-Shift Keying for Visible Light Communications

Monteiro

Hranilovic

2014

J. Lightwave Technol.

177

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Color-shift keying (CSK) is a visible light communication (VLC) intensity modulation scheme, outlined in IEEE 802.15.7, that transmits data imperceptibly through the variation of the light color emitted by a red, green, and blue (RGB) light emitting diode (LED). Unlike other intensity modulation schemes, CSK guarantees that the intensity of the luminary will not fluctuate, thus limiting potential human health complications related to flickering light.In this work, a rigorous design framework for CSK constellations is presented. The benefits of the frame work are that it can optimize constellations while accounting for cross talk between the color communication channels formed by the colored LEDs.Unlike previous works, the method applies the study of colorimetry to optimize higher order CSK constellations such that the luminary functions with a desired operating color, allowing constellations to be designed to meet lighting industry quality metrics.

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A probabilistic explanation of brightness scaling

Cited by 47 publications

References 30 publications

Responses of human visual cortex to uniform surfaces

Responses of human visual cortex to uniform surfaces

Perceiving the Intensity of Light.

Design and Implementation of Color-Shift Keying for Visible Light Communications

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