Dataset Information

A model of lightness perception guided by probabilistic assumptions about lighting and reflectance.

ABSTRACT: Lightness perception is the ability to perceive black, white, and gray surface colors in a wide range of lighting conditions and contexts. This ability is fundamental for any biological or artificial visual system, but it poses a difficult computational problem, and how the human visual system computes lightness is not well understood. Here I show that several key phenomena in lightness perception can be explained by a probabilistic graphical model that makes a few simple assumptions about local patterns of lighting and reflectance, and infers globally optimal interpretations of stimulus images. Like human observers, the model exhibits partial lightness constancy, codetermination, contrast, glow, and articulation effects. It also arrives at human-like interpretations of strong lightness illusions that have challenged previous models. The model's assumptions are reasonable and generic, including, for example, that lighting intensity spans a much wider range than surface reflectance and that shadow boundaries tend to be straighter than reflectance edges. Thus, a probabilistic model based on simple assumptions about lighting and reflectance gives a good computational account of lightness perception over a wide range of conditions. This work also shows how graphical models can be extended to develop more powerful models of constancy that incorporate features such color and depth.

SUBMITTER: Murray RF

PROVIDER: S-EPMC7424934 | biostudies-literature | 2020 Jul

REPOSITORIES: biostudies-literature

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A model of lightness perception guided by probabilistic assumptions about lighting and reflectance.

Murray Richard F RF

Journal of vision 20200701 7

Lightness perception is the ability to perceive black, white, and gray surface colors in a wide range of lighting conditions and contexts. This ability is fundamental for any biological or artificial visual system, but it poses a difficult computational problem, and how the human visual system computes lightness is not well understood. Here I show that several key phenomena in lightness perception can be explained by a probabilistic graphical model that makes a few simple assumptions about local ...[more]

PMID: 32725175

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Project description:(1) Background: Gangliogliomas comprise a small number of brain tumors. They usually present as World Health Organization (WHO) grade I, and they delineate on gadolinium-enhanced MRI; the surgical goal is wide radical resection, and the course thereafter is usually benign. Fluorescein sodium (FL) tends to accumulate in areas with altered blood-brain barrier (BBB). Thus far, the results provided by prospective and retrospective studies show that the utilization of this fluorophore may be associated with better visualization and improvement of resection for several tumors of the central nervous system. In this study, we retrospectively studied the effect of fluorescein sodium on visualization and resection of gangliogliomas. (2) Methods: Surgical databases in three neurosurgical departments (Regensburg University Hospital; Besta Institute, Milano, Italy; and Liv Hospital, Istanbul, Turkey), with approval by the local ethics committee, were retrospectively reviewed to find gangliogliomas surgically removed by a fluorescein-guided technique by the aid of a dedicated filter on the surgical microscope from April 2014 to February 2020. Eighteen patients (13 women, 5 men; mean age 22.9 years, range 3 to 78 years) underwent surgical treatment for gangliogliomas during 19 operations. Fluorescein was intravenously injected (5 mg/kg) after general anesthesia induction. Tumors were removed using a microsurgical technique with the YELLOW 560 Filter (YE560) (KINEVO/PENTERO 900, Carl Zeiss Meditec, Oberkochen, Germany). (3) Results: No side effects related to fluorescein occurred. In all tumors, contrast enhancement on preoperative MRI correlated with bright yellow fluorescence during the surgical procedure (17 gangliogliomas WHO grade I, 1 ganglioglioma WHO grade II). Fluorescein was considered helpful by the operating surgeon in distinguishing tumors from viable tissue in all cases (100%). Biopsy was intended in two operations, and subtotal resection was intended in one operation. In all other operations considered preoperatively eligible, gross total resection (GTR) was achieved in 12 out of 16 (75%) instances. (4) Conclusions: The use of FL and YE560 is a readily available method for safe fluorescence-guided tumor resection, possibly visualizing tumor margins intraoperatively similar to contrast enhancement in T1-weighted MRI. Our data suggested a positive effect of fluorescein-guided surgery on intraoperative visualization and extent of resection during resection of gangliogliomas.

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

A model of lightness perception guided by probabilistic assumptions about lighting and reflectance.

Publications

A model of lightness perception guided by probabilistic assumptions about lighting and reflectance.

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