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

Bachelor Thesis (2022)
Author(s)

T.M. Đào (TU Delft - Electrical Engineering, Mathematics and Computer Science)

Contributor(s)

E. Eisemann – Mentor (TU Delft - Computer Graphics and Visualisation)

Mark van de Ruit – Mentor (TU Delft - Computer Graphics and Visualisation)

CM Jonker – Graduation committee member (TU Delft - Interactive Intelligence)

Faculty
Electrical Engineering, Mathematics and Computer Science
Copyright
© 2022 Tan Đào
More Info
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Publication Year
2022
Language
English
Copyright
© 2022 Tan Đào
Graduation Date
24-06-2022
Awarding Institution
Delft University of Technology
Project
CSE3000 Research Project
Programme
Computer Science and Engineering
Faculty
Electrical Engineering, Mathematics and Computer Science
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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.

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