Journal of Terahertz Science and Electronic Information Technology , Volume. 20, Issue 10, 1087(2022)

Filtering approach for efficiently distributing render errors as a blue-noise

LIU Hongli* and HAN Honglei
Author Affiliations
  • [in Chinese]
  • show less

    The Monte Carlo(MC) integrators are the most commonly used approaches for numerically approximating radiant light energy propagating in virtual scenes. Distributing the Monte Carlo errors as blue-noise in the screen space significantly improves the visual fidelity. However, it is difficult to achieve such a goal efficiently for complex scenes with arbitrary sample counts and integration dimensionalities. A simple yet effective approach is proposed to deal with this problem. Firstly, bluenoise masks are adopted to scramble the quasi-random sequences, such that the rendering errors have a blue-noise spectrum at low sampling counts. Then, a filtering method is introduced, and the consequent rendering errors maintain the blue-noise spectrum at higher sample counts. Compared with several related works, the proposed method can efficiently obtain more stable blue noise results in different virtual scenes. The proposed method not only produces stable blue-noise errors but also has high computational efficiency, which is suitable for modern Monte Carlo-based renderers.

    Tools

    Get Citation

    Copy Citation Text

    LIU Hongli, HAN Honglei. Filtering approach for efficiently distributing render errors as a blue-noise[J]. Journal of Terahertz Science and Electronic Information Technology , 2022, 20(10): 1087

    Download Citation

    EndNote(RIS)BibTexPlain Text
    Save article for my favorites
    Paper Information

    Category:

    Received: Jul. 6, 2020

    Accepted: --

    Published Online: Dec. 26, 2022

    The Author Email: Hongli LIU (botregular@outlook.com)

    DOI:10.11805/tkyda2020448

    Topics