Dataset Information

The dynamic range of human lightness perception.

ABSTRACT: Natural viewing challenges the visual system with images that have a dynamic range of light intensity (luminance) that can approach 1,000,000:1 and that often exceeds 10,000:1 [1, 2]. The range of perceived surface reflectance (lightness), however, can be well approximated by the Munsell matte neutral scale (N 2.0/ to N 9.5/), consisting of surfaces whose reflectance varies by about 30:1. Thus, the visual system must map a large range of surface luminance onto a much smaller range of surface lightness. We measured this mapping in images with a dynamic range close to that of natural images. We studied simple images that lacked segmentation cues that would indicate multiple regions of illumination. We found a remarkable degree of compression: at a single image location, a stimulus luminance range of 5,905:1 can be mapped onto an extended lightness scale that has a reflectance range of 100:1. We characterized how the luminance-to-lightness mapping changes with stimulus context. Our data rule out theories that predict perceived lightness from luminance ratios or Weber contrast. A mechanistic model connects our data to theories of adaptation and provides insight about how the underlying visual response varies with context.

SUBMITTER: Radonjic A

PROVIDER: S-EPMC3244211 | biostudies-literature | 2011 Nov

REPOSITORIES: biostudies-literature

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The dynamic range of human lightness perception.

Radonjić Ana A Allred Sarah R SR Gilchrist Alan L AL Brainard David H DH

Current biology : CB 20111110 22

Natural viewing challenges the visual system with images that have a dynamic range of light intensity (luminance) that can approach 1,000,000:1 and that often exceeds 10,000:1 [1, 2]. The range of perceived surface reflectance (lightness), however, can be well approximated by the Munsell matte neutral scale (N 2.0/ to N 9.5/), consisting of surfaces whose reflectance varies by about 30:1. Thus, the visual system must map a large range of surface luminance onto a much smaller range of surface lig ...[more]

PMID: 22079116

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Project description:Brightness (perceived intensity) and lightness (perceived reflectance) matching were investigated in seven well-known visual stimuli that contain a visible shadow or transparent overlay. These stimuli are frequently upheld as evidence that low-level spatial filtering is inadequate to explain brightness/lightness illusions and that additional mid- or high-level mechanisms are required. The argument in favor of rejecting low-level spatial filtering explanations has been founded on the erroneous assumption that equating test patch and near surround luminance is sufficient to control for and rule out this type of mechanism. We tested this idea by comparing the matching behavior of four observers to the predictions of the ODOG multiscale filtering model (Blakeslee & McCourt, 1999). Lightness and brightness matching differed significantly only when test patches appeared in shadow or beneath a transparency. Lightness and brightness matches were both significantly larger under these conditions; however, the lightness matches greatly exceeded the brightness matches. Lightness matches were greater for test patches in shadow or beneath a transparency because lightness matches under these conditions were based on conscious inferential (not sensory-level) judgments where observers attempted to discount the difference in illumination. The ODOG model accounted for approximately 80% of the total variance in the brightness matches (as well as in the lightness matches for targets not in shadow or beneath a transparency), and successfully predicted the relative magnitude of these matches in five of the seven stimulus sets. These results indicate that multiscale spatial filtering provides a unified and parsimonious explanation for brightness perception in these stimuli and imply that higher-level mechanisms are not required to explain them. The model was not as successful for the argyle and wall of blocks illusions in that it incorrectly rank-ordered the relative magnitude of the effects across different versions of the stimuli. It is an important question whether such model failures are due to known but corrigible limitations of the ODOG model or whether they will require other (possibly higher-level) explanations.

Dataset Information

The dynamic range of human lightness perception.

Publications

The dynamic range of human lightness perception.

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