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    A Survey on Gradient-Domain Rendering

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    Date
    2019
    Author
    Hua, Binh-Son ORCID
    Gruson, Adrien ORCID
    Petitjean, Victor
    Zwicker, Matthias
    Nowrouzezahrai, Derek ORCID
    Eisemann, Elmar ORCID
    Hachisuka, Toshiya
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    Abstract
    Monte Carlo methods for physically-based light transport simulation are broadly adopted in the feature film production, animation and visual effects industries. These methods, however, often result in noisy images and have slow convergence. As such, improving the convergence of Monte Carlo rendering remains an important open problem. Gradient-domain light transport is a recent family of techniques that can accelerate Monte Carlo rendering by up to an order of magnitude, leveraging a gradient-based estimation and a reformulation of the rendering problem as an image reconstruction. This state of the art report comprehensively frames the fundamentals of gradient-domain rendering, as well as the pragmatic details behind practical gradient-domain uniand bidirectional path tracing and photon density estimation algorithms. Moreover, we discuss the various image reconstruction schemes that are crucial to accurate and stable gradient-domain rendering. Finally, we benchmark various gradient-domain techniques against the state-of-the-art in denoising methods before discussing open problems.
    BibTeX
    @article {10.1111:cgf.13652,
    journal = {Computer Graphics Forum},
    title = {{A Survey on Gradient-Domain Rendering}},
    author = {Hua, Binh-Son and Gruson, Adrien and Petitjean, Victor and Zwicker, Matthias and Nowrouzezahrai, Derek and Eisemann, Elmar and Hachisuka, Toshiya},
    year = {2019},
    publisher = {The Eurographics Association and John Wiley & Sons Ltd.},
    ISSN = {1467-8659},
    DOI = {10.1111/cgf.13652}
    }
    URI
    https://doi.org/10.1111/cgf.13652
    https://diglib.eg.org:443/handle/10.1111/cgf13652
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    Eurographics Association copyright © 2013 - 2023 
    Send Feedback | Contact - Imprint | Data Privacy Policy | Disable Google Analytics
    Theme by @mire NV
    System hosted at  Graz University of Technology.
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