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Cardinality-constrained texture filtering

Published: 21 July 2013 Publication History

Abstract

We present a method to create high-quality sampling filters by combining a prescribed number of texels from several resolutions in a mipmap. Our technique provides fine control over the number of texels we read per texture sample so that we can scale quality to match a memory bandwidth budget. Our method also has a fixed cost regardless of the filter we approximate, which makes it feasible to approximate higher-quality filters such as a Lánczos 2 filter in real-time rendering. To find the best set of texels to represent a given sampling filter and what weights to assign those texels, we perform a cardinality-constrained least-squares optimization of the most likely candidate solutions and encode the results of the optimization in a small table that is easily stored on the GPU. We present results that show we accurately reproduce filters using few texel reads and that both quality and speed scale smoothly with available bandwidth. When using four or more texels per sample, our image quality exceeds that of trilinear interpolation.

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Cited By

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  • (2020)High-Performance Image Filters via Sparse ApproximationsProceedings of the ACM on Computer Graphics and Interactive Techniques10.1145/34061823:2(1-19)Online publication date: 26-Aug-2020
  • (2016)Fast Filtering of Reflection ProbesComputer Graphics Forum10.5555/3071773.307178635:4(119-127)Online publication date: 1-Jul-2016
  • (2014)Bilinear accelerated filter approximationProceedings of the 25th Eurographics Symposium on Rendering10.1111/cgf.12410(33-40)Online publication date: 25-Jun-2014

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  1. Cardinality-constrained texture filtering

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      cover image ACM Transactions on Graphics
      ACM Transactions on Graphics  Volume 32, Issue 4
      July 2013
      1215 pages
      ISSN:0730-0301
      EISSN:1557-7368
      DOI:10.1145/2461912
      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: 21 July 2013
      Published in TOG Volume 32, Issue 4

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      Author Tags

      1. filter approximation
      2. image filtering
      3. image pyramid
      4. image resampling
      5. mipmap
      6. texture mapping

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      View all
      • (2020)High-Performance Image Filters via Sparse ApproximationsProceedings of the ACM on Computer Graphics and Interactive Techniques10.1145/34061823:2(1-19)Online publication date: 26-Aug-2020
      • (2016)Fast Filtering of Reflection ProbesComputer Graphics Forum10.5555/3071773.307178635:4(119-127)Online publication date: 1-Jul-2016
      • (2014)Bilinear accelerated filter approximationProceedings of the 25th Eurographics Symposium on Rendering10.1111/cgf.12410(33-40)Online publication date: 25-Jun-2014

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