Efficient Product Importance Sampling using Hierarchical Thresholding

We present an efficient method for importance sampling the product of multiple functions. Our algorithm computes a quick approximation of the product on-the-fly, based on hierarchical representations of the Local maxima and averages of the individual terms. Samples are generated by exploiting the hierarchical properties of many low-discrepancy sequences, and thresholded against the estimated product. We evaluate direct illumination by sampling the triple product of environment map lighting, surface reflectance, and a visibility function estimated per pixel. Our results show considerable noise reduction compared to existing state-of-the-art methods using only the product of lighting and BRDF.


Published in:
Proceedings of CGI 2008, 24, 7-9, 465-474
Presented at:
26th International Conference on Computer Graphics, Istanbul, TURKEY, June 9 - 11, 2008
Year:
2008
Keywords:
Laboratories:




 Record created 2012-06-04, last modified 2018-03-17

n/a:
Download fulltext
PDF

Rate this document:

Rate this document:
1
2
3
 
(Not yet reviewed)