TUTCRIS - Tampereen teknillinen yliopisto

TUTCRIS

Blockwise Multi-Order Feature Regression for Real-Time Path Tracing Reconstruction

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Yksityiskohdat

AlkuperäiskieliEnglanti
JulkaisuACM TRANSACTIONS ON GRAPHICS
DOI - pysyväislinkit
TilaHyväksytty/In press - 19 huhtikuuta 2019
OKM-julkaisutyyppiA1 Alkuperäisartikkeli

Tiivistelmä

Path tracing produces realistic results including global illumination using a unified simple rendering pipeline. Reducing the amount of noise to imperceptible levels without post-processing requires thousands of samples per pixel (spp), while currently it is only possible to render extremely noisy 1 spp frames in real time with desktop GPUs. However, post-processing can utilize feature buffers, which contain noise-free auxiliary data available in the rendering pipeline. Previously, regression-based noise filtering methods have only been used in offline rendering due to their high computational cost. In this paper we propose a novel regression-based reconstruction pipeline, called Blockwise Multi-Order Feature Regression (BMFR), tailored for path-traced 1 spp inputs that runs in real time. The high speed is achieved with a fast implementation of augmented QR factorization and by using stochastic regularization to address rank-deficient feature data. The proposed algorithm is 1.8× faster than the previous state-of-the-art real-time path tracing reconstruction method while producing better quality frame sequences.

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