Efficient product sampling using hierarchical thresholding
Författare
Summary, in Swedish
Abstract in Undetermined
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.
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.
Avdelning/ar
Publiceringsår
2008
Språk
Engelska
Sidor
465-474
Publikation/Tidskrift/Serie
Visual Computer
Volym
24
Issue
7-9
Dokumenttyp
Artikel i tidskrift
Förlag
Springer
Ämne
- Computer Science
Nyckelord
- importance sampling
- rejection sampling
- multiple functions
- ray tracing
- visibility
Status
Published
Forskningsgrupp
- Computer Graphics
ISBN/ISSN/Övrigt
- ISSN: 0178-2789