Paz, Valeriano Ferreras
(Robert Bosch GmbH, Center of Competence Optics, Car Multimedia, Renningen, 71272, Germany)
,
Kohlenbecker, Stephan
(Robert Bosch GmbH, Center of Competence Optics, Car Multimedia, Renningen, 71272, Germany)
,
Persidis, Efstathios
(Robert Bosch GmbH, Center of Competence Optics, Car Multimedia, Renningen, 71272, Germany)
To ensure end-user readability, displays exposed to sunlight need special surface treatments. Especially in automotive applications, rough antiglare (AG) surface treatments are applied to the top surface. However, a rough surface on top of a brilliant display has a direct impact on its image quality...
To ensure end-user readability, displays exposed to sunlight need special surface treatments. Especially in automotive applications, rough antiglare (AG) surface treatments are applied to the top surface. However, a rough surface on top of a brilliant display has a direct impact on its image quality. Carefully designing the AG surface allows a compromise between reflection suppression and image quality. One of the undesired effects is the so-called “visual sparkling”, where the displayed image appears to show an uneven luminance distribution especially in areas where solid colors are shown. This effect itself is quite subjective for that it is necessary to quantify it in a reproducible way. In this work, we present a simple yet effective method for characterization of the sparkle effect based on the evaluation of image uniformity with help of grey-value histogram extraction and fitting with a simple normal distribution.
To ensure end-user readability, displays exposed to sunlight need special surface treatments. Especially in automotive applications, rough antiglare (AG) surface treatments are applied to the top surface. However, a rough surface on top of a brilliant display has a direct impact on its image quality. Carefully designing the AG surface allows a compromise between reflection suppression and image quality. One of the undesired effects is the so-called “visual sparkling”, where the displayed image appears to show an uneven luminance distribution especially in areas where solid colors are shown. This effect itself is quite subjective for that it is necessary to quantify it in a reproducible way. In this work, we present a simple yet effective method for characterization of the sparkle effect based on the evaluation of image uniformity with help of grey-value histogram extraction and fitting with a simple normal distribution.
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