“Fast Path Space Filtering by Jittered Spatial Hashing”
Conference:
Type:
Entry Number: 73
Title:
- Fast Path Space Filtering by Jittered Spatial Hashing
Presenter(s)/Author(s):
Abstract:
Restricting path tracing to a small number of paths per pixel for performance reasons rarely achieves a satisfactory image quality for scenes of interest. However, path space filtering may dramatically improve the visual quality by sharing information across vertices of paths classified as “nearby”. While thus contributions can be filtered in path space and beyond the first intersection, searching “nearby” paths is more expensive than filtering in screen space. We greatly improve over this performance penalty by storing and looking up the required information in a hash map using hash keys constructed from jittered and quantized information, such that only a single query may replace costly neighborhood searches.
References:
P. Gautron, M. Droske, C. Wáchter, L. Kettner, A. Keller, N. Binder, and K. Dahm. 2014. Path Space Similarity Determined by Fourier Histogram Descriptors. In ACM SIGGRAPH 2014 Talks (SIGGRAPH ’14). ACM, New York, NY, USA, Article 39, 1 pages.
A. Keller, K. Dahm, and N. Binder. 2014. Path Space Filtering. In ACM SIGGRAPH 2014 Talks (SIGGRAPH ’14). ACM, New York, NY, USA, Article 68, 1 pages.
J. Munkberg, J. Hasselgren, P. Clarberg, M. Andersson, and T. Akenine-Möller. 2016. Texture Space Caching and Reconstruction for Ray Tracing. ACM Trans. Graph. 35, 6, Article 249 (Nov. 2016), 13 pages.
P. Sen, M. Zwicker, F. Rousselle, S.-E.Yoon, and N. Kalantari. 2015. Denoising Your Monte Carlo Renders: Recent Advances in Image-space Adaptive Sampling and Reconstruction. In ACM SIGGRAPH 2015 Courses (SIGGRAPH ’15). ACM, New York, NY, USA, Article 11, 255 pages.
