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Practical Noise Reduction for Progressive Stochastic Ray Tracing with Perceptual Control
Nov.-Dec. 2012 (vol. 32 no. 6)
pp. 46-55
| ASCII Text | x | ||
| Karsten Schwenk, Arjan Kuijper, Johannes Behr, Dieter W. Fellner, "Practical Noise Reduction for Progressive Stochastic Ray Tracing with Perceptual Control," IEEE Computer Graphics and Applications, vol. 32, no. 6, pp. 46-55, Nov.-Dec., 2012. | |||
| BibTex | x | ||
| @article{ 10.1109/MCG.2012.30, author = {Karsten Schwenk and Arjan Kuijper and Johannes Behr and Dieter W. Fellner}, title = {Practical Noise Reduction for Progressive Stochastic Ray Tracing with Perceptual Control}, journal ={IEEE Computer Graphics and Applications}, volume = {32}, number = {6}, issn = {0272-1716}, year = {2012}, pages = {46-55}, doi = {http://doi.ieeecomputersociety.org/10.1109/MCG.2012.30}, publisher = {IEEE Computer Society}, address = {Los Alamitos, CA, USA}, } | |||
| RefWorks Procite/RefMan/Endnote | x | ||
| TY - MGZN JO - IEEE Computer Graphics and Applications TI - Practical Noise Reduction for Progressive Stochastic Ray Tracing with Perceptual Control IS - 6 SN - 0272-1716 SP46 EP55 EPD - 46-55 A1 - Karsten Schwenk, A1 - Arjan Kuijper, A1 - Johannes Behr, A1 - Dieter W. Fellner, PY - 2012 KW - Noise abatement KW - Rendering (computer graphics) KW - Noise level KW - Interactive systems KW - Image edge detection KW - Lighting KW - Noise measurement KW - Ray tracing KW - illumination filtering KW - Noise abatement KW - Rendering (computer graphics) KW - Noise level KW - Interactive systems KW - Image edge detection KW - Lighting KW - Noise measurement KW - Ray tracing KW - computer graphics KW - noise reduction KW - stochastic ray tracing KW - progressive rendering VL - 32 JA - IEEE Computer Graphics and Applications ER - | |||
DOI Bookmark: http://doi.ieeecomputersociety.org/10.1109/MCG.2012.30
A proposed method reduces noise in stochastic ray tracing for interactive progressive rendering. The method accumulates high-variance light paths in a separate buffer, which is filtered by a high-quality edge-preserving filter. Then, this method adds a combination of the noisy unfiltered samples and the less noisy (but biased) filtered samples to the low-variance samples to form the final image. A novel per-pixel blending operator combines both contributions in a way that respects a user-defined threshold on perceived noise. This method can provide fast, reliable previews, even in the presence of complex features such as specular surfaces and high-frequency textures. At the same time, it's consistent in that the bias due to filtering vanishes in the limit.
Index Terms:
Noise abatement,Rendering (computer graphics),Noise level,Interactive systems,Image edge detection,Lighting,Noise measurement,Ray tracing,illumination filtering,Noise abatement,Rendering (computer graphics),Noise level,Interactive systems,Image edge detection,Lighting,Noise measurement,Ray tracing,computer graphics,noise reduction,stochastic ray tracing,progressive rendering
Citation:
Karsten Schwenk, Arjan Kuijper, Johannes Behr, Dieter W. Fellner, "Practical Noise Reduction for Progressive Stochastic Ray Tracing with Perceptual Control," IEEE Computer Graphics and Applications, vol. 32, no. 6, pp. 46-55, Nov.-Dec. 2012, doi:10.1109/MCG.2012.30
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