“Attribute-preserving gamut mapping of measured BRDFs” by Sun, Serrano, Gutierrez and Masia

  • ©Tiancheng Sun, Ana Serrano, Diego Gutierrez, and Belen Masia

  • ©Tiancheng Sun, Ana Serrano, Diego Gutierrez, and Belen Masia

  • ©Tiancheng Sun, Ana Serrano, Diego Gutierrez, and Belen Masia

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Entry Number: 69

Title:

    Attribute-preserving gamut mapping of measured BRDFs

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Abstract:


    Real-world materials present a wide variety of appearances, commonly described in computer graphics with the bidirectional reflectance distribution function (BRDF). Printers, on the other hand, have a predefined set of only a few inks, which defines the printer’s gamut. As a consequence of this limitation, many materials cannot be exactly reproduced by the printer, creating distortions in the printed appearance that are hard to control. Finding the best approximation of the input BRDF that falls within the printer’s gamut while minimizing such distortions as much as possible is the problem known as gamut mapping. We present a novel two-step gamut mapping algorithm that allows users to specify which perceptual attribute of the original material they want to preserve. In the first step, we work in the low-dimensional intuitive appearance space recently proposed by Serrano et al. [Serrano et al. 2016], and adjust achromatic reflectance via an objective function that strives to preserve certain attributes. From such intermediate representation, we then perform an image-based optimization including color information, to bring the BRDF into gamut. We show how our method yields superior results compared to the state of the art, with the additional advantage that the user can specify which visual attributes need to be preserved. For more details we refer to the reader to the full paper [Sun et al. 2017].

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Acknowledgements:


    This work has been partially funded by an ERC Consolidator Grant (project CHAMELEON), the Spanish Ministry of Economy and Competitiveness (projects TIN2016-79710-P and TIN2016-78753-P, and an FPI grant), and the Tsinghua Spark Program.


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