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Wide Gamut Moment-based Constrained Spectral Uplifting

Publication at Faculty of Mathematics and Physics |
2022

Abstract

Spectral rendering is increasingly used in appearance-critical rendering workflows due to its ability to predict colour values under varying illuminants. However, directly modelling assets via input of spectral data is a tedious process: and if asset appearance is defined via artist-created textures, these are drawn in colour space, i.e.

RGB. Converting these RGB values to equivalent spectral representations is an ambiguous problem, for which robust techniques have been proposed only comparatively recently.

However, other than the resulting RGB values matching under the illuminant the RGB space is defined for (usually D65), these uplifting techniques do not provide the user with further control over the resulting spectral shape. In a recent publication, we have proposed a method for constraining the spectral uplifting process so that for a finite number of input spectra that need to be preserved, it always yields the correct uplifted spectrum for the corresponding RGB value.

We extend this previous work, which supported the sRGB gamut only, by describing a method that is able to constrain any spectrum from within the gamut of realisable reflectances. Due to constraints placed on the uplifting process, target RGB values that are in close proximity to one another uplift to spectra within the same metameric family, so that textures with colour variations can be meaningfully uplifted.

Renderings uplifted via our method show minimal discrepancies when compared to the original objects.