Presentation + Paper
2 May 2018 Modeling the effect of macular pigment enhancement on vision in degraded visual environments (DVE)
Author Affiliations +
Abstract
The macular pigment (MP) is an accumulation of lutein and zeaxanthin, carotenoids derived from dietary sources, which is primarily in the central 15° of the human visual field. MP absorbs light in the 400 to 520 nm range. Consequently the MP is a spectral filter over the photoreceptors, reducing the effects of internally scattered light and attenuating the short wavelength component of natural sunlight. The between-subject average MP optical density (OD) is about 0.2 to 0.6 log units depending on the sample population, while the range of MPOD is reportedly 0 to 1.5 log units. Some people can increase their MPOD by increasing their consumption of lutein and zeaxanthin, and this may be important for vision in DVE. Specifically, nutritional interventions and dietary supplements have produced statistically significant enhancements under laboratory conditions in visual tasks such as visibility through haze, low contrast target detection, contrast sensitivity, glare resistance and recovery, photostress recovery, dark adaptation, mesopic sensitivity, and enhanced reaction times. The question is whether these enhancements are operationally meaningful or not. The present paper begins to address the question by modeling MPOD effects on the visibility to low contrast targets seen under a range of DVE over realistic distances that incorporate atmospheric filtering. Specific model parameters include luminance, target contrast, spectral content, and distance. The model can be extended to estimate the efficacy of MPOD effects on target detection, discrimination, and standoff distances.
Conference Presentation
© (2018) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.
Kevin O’Brien, Leonard A. Temme, and Paul St. Onge "Modeling the effect of macular pigment enhancement on vision in degraded visual environments (DVE)", Proc. SPIE 10642, Degraded Environments: Sensing, Processing, and Display 2018, 1064204 (2 May 2018); https://doi.org/10.1117/12.2304371
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CITATIONS
Cited by 1 scholarly publication.
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KEYWORDS
Visualization

Driver's vision enhancers

Visual process modeling

Enhanced vision

Atmospheric modeling

Target detection

Visibility

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