1 Centre de Visiò per Computador, Universitat Autònoma de Barcelona
2 Universidade da Coruña, CITIC 3 GIST
Teaser
VPT results generated using the same source volume but during the interactive manipulation of different DVR transfer functions. Multiple scattering bounces per ray are simulated.
Our real-time denoising improves VPT images (MC-DVR with only 2 spp) while reducing its noise effectively. Offline VPT with 1024 spp, taking minutes to produce a single image, is shown as reference.
Abstract
Direct Volume Rendering (DVR) using Volumetric Path Tracing (VPT) is a scientific visualization technique that simulates light
transport with objects' matter using physically-based lighting models. Monte Carlo (MC) path tracing is often used with surface models, yet
its application for volumetric models is difficult due to the complexity of integrating MC light-paths in volumetric media with none or smooth
material boundaries. Moreover, auxiliary geometry-buffers (G-buffers) produced for volumes are typically very noisy, failing to guide image
denoisers relying on that information to preserve image details. This makes existing real-time denoisers, which take noise-free G-buffers
as their input, less effective when denoising VPT images. We propose the necessary modifications to an image-based denoiser previously
used when rendering surface models, and demonstrate effective denoising of VPT images. In particular, our denoising exploits temporal
coherence between frames, without relying on noise-free G-buffers, which has been a common assumption of existing denoisers for
surface-models. Our technique preserves high-frequency details through a weighted recursive least squares that handles heterogeneous
noise for volumetric models. We show for various real data sets that our method improves the visual fidelity and temporal stability of VPT
during classic DVR operations such as camera movements, modifications of the light sources, and editions to the volume transfer function.
@Article{Iglesias-Guitian:2020:RTD,
author = {{Jos\'e Antonio} {Iglesias Guiti\'an} and Prajita Mane and Bochang Moon},
title = {Real-Time Denoising of Monte Carlo Path Tracing for Direct Volume Rendering},
journal = {IEEE Transactions on Visualization and Computer Graphics},
year = {2020},
volume = {},
number = {},
pages = {1-1},
doi = {10.1109/TVCG.2020.3037680}
}
Acknowledgments
The authors would like to thank reviewers for their insightful feedback.
We also thank S. Oh, F. Lumbreras and J. Serrat for their help with Tensorflow, and T. Kroes for Exposure Render.
The datasets are courtesy of the OsiriX Foundation (MANIX), University of Texas (CHAMELEON), University of Arizona (HELODERMA) and XYZ RGB Inc. (DRAGON).
This work has received funding from the European Union's Horizon 2020 research and innovation programme under the Marie Skłodowska-Curie g.a. No 665919.
J.A. Iglesias-Guitian acknowledges the UDC-Inditex InTalent programme, the Spanish Ministry project TIN2017-88709-R, RYC2018-025385-I (MCIU/AEI/FEDER, EU), FEDER Galicia ED431G 2019/01 and the Nvidia GPU Grant Program.
B. Moon was supported by The Cross-Ministry Giga KOREA Project grant funded by the Korea government (MSIT) (No. GK20P0300).
