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Open Access A translucency classification for computer graphics

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Translucency is a visual property attributed to objects that light may cross without transmitting a clear image of the scene which is behind. In absence of a more precise definition, this perceptual attribute is often considered as an intermediate between transparency, which is the property of objects that light may cross by transmitting a clear image of the scene behind, and opacity, which is the property of blocking the transmission of light and therefore masking completely the scene behind. If it is rather clear that translucency is closely related to light scattering, it is difficult to classify the translucent appearance according to one scale only, due to the different types of scattering, which can occur as well as the role of absorbance and thickness of the material. Through synthetic images rendered by optical models, we show that surface scattering, volume (or subsurface) scattering, possibly mixed with selective absorption, produce different types of translucency effects and different intermediates between transparency and opacity. We thus propose to represent translucency according to three axes related to these three optical phenomena: surface scattering, volume scattering, and absorption.
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Keywords: Image synthesis; Light scattering; Opacity; Translucency; Transparency

Document Type: Research Article

Publication date: January 13, 2019

This article was made available online on January 13, 2019 as a Fast Track article with title: "A translucency classification for computer graphics".

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  • For more than 30 years, the Electronic Imaging Symposium has been serving those in the broad community - from academia and industry - who work on imaging science and digital technologies. The breadth of the Symposium covers the entire imaging science ecosystem, from capture (sensors, camera) through image processing (image quality, color and appearance) to how we and our surrogate machines see and interpret images. Applications covered include augmented reality, autonomous vehicles, machine vision, data analysis, digital and mobile photography, security, virtual reality, and human vision. IS&T began sole sponsorship of the meeting in 2016. All papers presented at EIs 20+ conferences are open access.

    Please note: For purposes of its Digital Library content, IS&T defines Open Access as papers that will be downloadable in their entirety for free in perpetuity. Copyright restrictions on papers vary; see individual paper for details.

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