Achieving Perceptually-Acceptable Early Renders in Spectral Progressive Rendering by Introducing Bias

Bachelor thesis (2022)

Authors

T.M. Đào Electrical Engineering, Mathematics and Computer Science

Contributors

E. Eisemann Computer Graphics and Visualisation - EEMCS (mentor)
M. van de Ruit Computer Graphics and Visualisation - EEMCS (mentor)
C.M. Jonker Interactive Intelligence - EEMCS (graduation committee member)
Faculty
Electrical Engineering, Mathematics and Computer Science, Electrical Engineering, Mathematics and Computer Science
Copyright: © 2022 Tan Đào
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Published Date

24-06-2022

Language

English

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Faculty

Electrical Engineering, Mathematics and Computer Science

Abstract

Spectral Monte-Carlo rendering can simulate advanced light phenomena (e.g., dispersion, caustics, or iridescence), but require significantly more samples compared to trichromatic rendering to obtain noise-free images. Therefore, its progressive variant typically exhibits an extreme amount of chromatic noise in early renders. To that end, we propose a two-stage progressive approach. We initially restrict the original wavelength distribution, then slowly relax it. In the process of relaxing the range of wavelengths, all wavelengths that are outside of that restricted range will be propagated. Thereby, we lower variance and increase the perception of these early renders with little overhead.