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Fast hierarchical importance sampling with blue noise properties

Published: 01 August 2004 Publication History

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.

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      cover image ACM Transactions on Graphics
      ACM Transactions on Graphics  Volume 23, Issue 3
      August 2004
      684 pages
      ISSN:0730-0301
      EISSN:1557-7368
      DOI:10.1145/1015706
      Issue’s Table of Contents
      Permission to make digital or hard copies of all or part of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for components of this work owned by others than ACM must be honored. Abstracting with credit is permitted. To copy otherwise, or republish, to post on servers or to redistribute to lists, requires prior specific permission and/or a fee. Request permissions from [email protected]

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      Publication History

      Published: 01 August 2004
      Published in TOG Volume 23, Issue 3

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      Author Tags

      1. Blue Noise
      2. Deterministic Sampling
      3. Digital Halftoning
      4. Environment Mapping
      5. Fibonacci Number System
      6. Hierarchical Representation
      7. Importance Sampling
      8. Lookup Table-based Techniques
      9. Penrose Tiling
      10. Rendering

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