Real-Time Denoising of Volumetric Path Tracing for Direct Volume Rendering

Jose A. Iglesias-Guitian 1, 2 , Prajita Mane 3 , Bochang Moon 3

Centre de Visiò per Computador, Universitat Autònoma de Barcelona 1 , University of A Coruña - CITIC 2 , Gwangju Institute of Science and Technology 3

In IEEE Transactions on Visualization and Computer Graphics (TVCG)

Real-Time Denoising of Volumetric Path Tracing for Direct Volume Rendering
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.


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.

Video (available to download in the last section)