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Enhancing Contrast-Sensitivity Charts for Validating Visual Representations of Low-Illumination Scenes
Technical Paper
2019-01-1009
ISSN: 0148-7191, e-ISSN: 2688-3627
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Abstract
This aim of this study was to introduce and test three different design enhancements to the contrast-sensitivity charts developed by Ayers and Kubose [1]. Contrast-sensitivity charts are the current, critical instrument for generating photographic representations of low-illumination scenes. However, their range of applicability is limited to a specific range of lighting conditions for any given scene, and a limited set of testing and perceptual conditions for observers. A total of four contrast charts were presented to ten dark-adapted observers in nine different lighting conditions that changed in ascending order from low to high levels of illumination. For each lighting condition, the order and orientation of the charts was randomized. Observations related to the number of detected contrast levels were then compared to find the utilization ranges for each chart. In addition, observers were asked to report the directionality of the detected center light wedges for the two enhanced chart designs. The non-linear contrast functions minimized floor and ceiling effects, specifically at the lower tested frequencies of 3.5 and 7.0 c/d. Additionally, the wedge orientation of each visual target added a layer of testability for the perception of contrast and the validation of visual representations. The inclusion of non-linear contrast functions, randomized contrast levels, and a re-orientable layout extended the usefulness and range of lighting in which contrast-sensitivity charts can be used. The described enhanced contrast-sensitivity charts provide testable means to validate photographic representations of low-illumination scenes for an extended range of lighting and testing conditions.
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Sprague, J., Meza-Arroyo, M., Shibata, P., and Auflick, J., "Enhancing Contrast-Sensitivity Charts for Validating Visual Representations of Low-Illumination Scenes," SAE Technical Paper 2019-01-1009, 2019, https://doi.org/10.4271/2019-01-1009.Data Sets - Support Documents
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