Ambient Light Compensation Through Adaptive Visual Modeling

Metadata

Publisher: SMPTE
Doc Type: Journal Article
Content Type: Original Research
Abbreviated Title: SMPTE Motion Imaging Jour.
Volume: 133, No. 4, pp. 16–22
Abstract: Ambient light can significantly degrade picture quality by reducing visibility of details and contrast. In many cases, it is difficult to control or eliminate ambient light, making it essential to compensate for its effect. This is especially true in the context of media and entertainment, where viewers often consume content in different lighting conditions and environments. Traditional image processing techniques, such as adjusting the backlight, brightness/contrast, or more professionally using a PLUGE signal, do not sufficiently model the human visual system. The result is that detail is lost under changes in ambient light. This is especially problematic for very dark scenes, which have become apparent with cinematic high dynamic range content. This paper proposes a method of ambient light compensation by adaptively modeling the contrast sensitivity functions of the human visual system. By estimating global eye adaptation to both the content and the surround environment, the contrast sensitivity models may be used to maintain perceptual detail and contrast under varying ambient illumination. We build upon existing models of human vision and show how we can use cone sensitivity to maintain global contrast. Since displays have limited dynamic range, we show how this can be adaptive to the content and environment.
Publication Date: 2024-07-01
DOI: 10.5594/JMI.2024/QHIF9784
ISSN: Print: 1545-0279 | Electronic: 2160-2492
Link: https://doi.org/10.5594/JMI.2024/QHIF9784
Author(s): Jaclyn Pytlarz
Keyword(s): Ambient, Light, Contrast, Perception, Media
Copyright: © 2024 SMPTE

Bibliographic Reference(s)

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Objectively Evaluating High Dynamic Range and Wide Color Gamut Color Differences [Active]
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ITU-R BT.2100-2 [Active]
SMPTE ST 2084:2014 [Active, Stabilized]

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Jaclyn Pytlarz; Ambient Light Compensation Through Adaptive Visual Modeling, MIJ 2024, Volume 133, Number 4 (pp. 16 to 22); SMPTE, 2024. Available at https://doi.org/10.5594/JMI.2024/QHIF9784

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Jaclyn Pytlarz; Ambient Light Compensation Through Adaptive Visual Modeling, MIJ 2024, Volume 133, Number 4 (pp. 16 to 22); SMPTE, 2024. Available at https://doi.org/10.5594/JMI.2024/QHIF9784

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Jaclyn Pytlarz; Ambient Light Compensation Through Adaptive Visual Modeling, MIJ 2024, Volume 133, Number 4 (pp. 16 to 22); SMPTE, 2024. Available at https://doi.org/10.5594/JMI.2024/QHIF9784

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<span class="citation">Jaclyn Pytlarz; <cite>Ambient Light Compensation Through Adaptive Visual Modeling</cite>, MIJ 2024, Volume 133, Number 4 (pp. 16 to 22); SMPTE, 2024. Available at <a href="https://doi.org/10.5594/JMI.2024/QHIF9784" target="_blank" rel="noopener">https://doi.org/10.5594/JMI.2024/QHIF9784</a></span>

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Jaclyn Pytlarz; Ambient Light Compensation Through Adaptive Visual Modeling, MIJ 2024, Volume 133, Number 4 (pp. 16 to 22); SMPTE, 2024
doi: 10.5594/JMI.2024/QHIF9784
url: https://doi.org/10.5594/JMI.2024/QHIF9784

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Jaclyn Pytlarz; <cite id="bib-10-5594-jmi-2024-qhif9784">Ambient Light Compensation Through Adaptive Visual Modeling</cite>, MIJ 2024, Volume 133, Number 4 (pp. 16 to 22); SMPTE, 2024
<span class="doi">10.5594/JMI.2024/QHIF9784</span>
</li>