NPAR2017

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Mixed Illumination Analysis in Single Image for Interactive Color Grading
(Association for Computing Machinery, Inc (ACM), 2017) Duchêne, Sylvain; Aliaga, Carlos; Pouli, Tania; Pérez, Patrick; Holger Winnemoeller and Lyn Bartram
Colorists often use keying or rotoscoping tools to access and edit particular colors or parts of the scene. Although necessary, this is a time-consuming and potentially imprecise process, as it is not possible to fully separate the influence of light sources in the scene from the colors of objects and actors within it. To simplify this process, we present a new solution for automatically estimating the color and influence of multiple illuminants, based on image variation analysis. Using this information, we present a new color grading tool for simply and interactively editing the colors of de- tected illuminants, which fits naturally in color grading workflows. We demonstrate the use of our solution in several scenes, evaluating the quality of our results by means of a psychophysical study.