Overview   Tree   Index 
NPR Literature
PREV  NEXT FRAMES  NO FRAME 

[ODJ+04]  Fast Hierarchical Importance Sampling with Blue Noise Properties

Ostromoukhov:2004:FHI (Article)
Author(s)Ostromoukhov V., Donohue C. and Jodoin P.M.
Title« Fast Hierarchical Importance Sampling with Blue Noise Properties »
JournalACM Transactions on Graphics, Proceedings of ACM SIGGRAPH 2004 (Los Angeles, CA, August 8--12, 2004)
Volume23
Number3
Page(s)488--495
Year2004
URLhttp://www.iro.umontreal.ca/~ostrom/publications/abstracts.html

Abstract
This paper presents a novel method for efficiently generating a good sampling pattern given an importance density over a 2D domain. A Penrose tiling is hierarchically subdivided creating a sufficiently large number of sample points. These points are numbered using the Fibonacci number system, and these numbers are used to threshold the samples against the local value of the importance density. Pre-computed correction vectors, obtained using relaxation, are used to improve the spectral characteristics of the sampling pattern. The technique is deterministic and very fast; the sampling time grows linearly with the required number of samples. We illustrate our technique with importance-based environment mapping, but the technique is versatile enough to be used in a large variety of computer graphics applications, such as light transport calculations, digital halftoning, geometry processing, and various rendering techniques.

BibTeX code
@article{Ostromoukhov:2004:FHI,
  number = {3},
  volume = {23},
  optwww = {},
  author = {Victor Ostromoukhov and Charles Donohue and Pierre-Marc Jodoin},
  optkey = {},
  optstatus = {},
  url = {http://www.iro.umontreal.ca/~ostrom/publications/abstracts.html},
  localfile = {papers/Ostromoukhov.2004.FHI.pdf},
  abstract = {This paper presents a novel method for efficiently generating a
              good sampling pattern given an importance density over a 2D
              domain. A Penrose tiling is hierarchically subdivided creating a
              sufficiently large number of sample points. These points are
              numbered using the Fibonacci number system, and these numbers are
              used to threshold the samples against the local value of the
              importance density. Pre-computed correction vectors, obtained
              using relaxation, are used to improve the spectral characteristics
              of the sampling pattern. The technique is deterministic and very
              fast; the sampling time grows linearly with the required number of
              samples. We illustrate our technique with importance-based
              environment mapping, but the technique is versatile enough to be
              used in a large variety of computer graphics applications, such as
              light transport calculations, digital halftoning, geometry
              processing, and various rendering techniques.},
  title = {{F}ast {H}ierarchical {I}mportance {S}ampling with {B}lue {N}oise
           {P}roperties},
  optmonth = {},
  doi = {http://doi.acm.org/10.1145/1015706.1015750},
  journal = SIGGRAPH2004,
  year = {2004},
  pages = {488--495},
}

 Overview   Tree   Index 
NPR Literature
PREV  NEXT FRAMES  NO FRAME 

Submit a bug

This document was generated by bib2html 3.3.
Copyright © 1998-05 Stéphane GALLAND (under the GNU General Public License)

Valid HTML 4.01!Valid CSS!