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Filtering color mapped textures and surfaces

Published: 21 March 2013 Publication History

Abstract

Color map textures applied directly to surfaces, to geometric microsurface details, or to procedural functions (such as noise), are commonly used to enhance visual detail. Their simplicity and ability to mimic a wide range of realistic appearances have led to their adoption in many rendering problems. As with any textured or geometric detail, proper filtering is needed to reduce aliasing when viewed across a range of distances, but accurate and efficient color map filtering remains an open problem for several reasons: color maps are complex non-linear functions, especially when mapped through procedural noise and/or geometry-dependent functions, and the effects of perspective and masking further complicate the filtering over a pixel's footprint. We accurately solve this problem by computing and sampling from specialized filtering distributions on-the-fly, yielding very fast performance. We filter color map textures applied to (macro-scale) surfaces, as well as color maps applied according to (micro-scale) geometric details. We introduce a novel representation of a (potentially modulated) color map's distribution over pixel footprints using Gaussian statistics and, in the more complex case of high-resolution color mapped microsurface details, our filtering is view- and light-dependent, and capable of correctly handling masking and occlusion effects. Our results match ground truth and our solution is well suited to real-time applications, requires only a few lines of shader code (provided in supplemental material), is high performance, and has a negligible memory footprint.

Supplementary Material

JPG File (p129-heitz.jpg)
Supplemental files. (p129-heitz_supp.pdf)
Supplemental files.
AVI File (p129-heitz.avi)

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      cover image ACM Conferences
      I3D '13: Proceedings of the ACM SIGGRAPH Symposium on Interactive 3D Graphics and Games
      March 2013
      242 pages
      ISBN:9781450319560
      DOI:10.1145/2448196
      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: 21 March 2013

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      Author Tags

      1. Gaussian statistics
      2. LOD
      3. noise
      4. procedural texture

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