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Boosting Histogram-Based Denoising Methods with GPU Optimizations

  • We propose a high-performance GPU implementation of Ray Histogram Fusion (RHF), a denoising method for stochastic global illumination rendering. Based on the CPU implementation of the original algorithm, we present a naive GPU implementation and the necessary optimization steps. Eventually, we show that our optimizations increase the performance of RHF by two orders of magnitude when compared to the original CPU implementation and one order of magnitude compared to the naive GPU implementation. We show how the quality for identical rendering times relates to unfiltered path tracing and how much time is needed to achieve identical quality when compared to an unfiltered path traced result. Finally, we summarize our work and describe possible future applications and research based on this.

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Metadaten
Document Type:Conference Object
Language:English
Author:Sebastian Szeracki, Thorsten Roth, André Hinkenjann, Yongmin Li
Parent Title (English):Hinkenjann, Maiero et al. (Hg.): Virtuelle und Erweiterte Realität. 12. Workshop der GI-Fachgruppe VR/AR
First Page:113
Last Page:124
ISBN:978-3-8440-3868-2
URL:https://vc.inf.h-bonn-rhein-sieg.de/basilic/Publications/2015/SRHL15/
Publication year:2015
Tag:CUDA; Computer Graphics; Global Illumination; Image Processing
Departments, institutes and facilities:Fachbereich Informatik
Institute of Visual Computing (IVC)
Dewey Decimal Classification (DDC):0 Informatik, Informationswissenschaft, allgemeine Werke / 00 Informatik, Wissen, Systeme / 004 Datenverarbeitung; Informatik
Entry in this database:2015/09/09