A cost-effective supersampling for full scene antialiasing

Byung Uck Kim, Woo Chan Park, Sung Bong Yang, Tack Don Han

Research output: Chapter in Book/Report/Conference proceedingChapter

Abstract

We present a graphics hardware system to implement supersampling cost-effectively. Supersampling is the well-known technique to produce high quality images. However, rendering the scene at a higher resolution requires a large amount of memory size and memory bandwidth. Such costs can be alleviated by grouping subpixels into a fragment with a coverage mask which indicates which part of the pixel is covered. However, this may cause color distortion when several objects either overlap or intersect with each other within a pixel. In order to minimize such errors, we introduce an extra buffer, called the RuF(Recently used Fragment)-buffer, for storing the footprint of a fragment most recently used in the color manipulation. In our experiments, the proposed system can produce high quality images as good as supersampling with a smaller amount of memory size and memory bandwidth, compared with the conventional supersampling.

Original languageEnglish
Title of host publicationLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
EditorsPen-Chung Yew, Jingling Xue
PublisherSpringer Verlag
Pages271-281
Number of pages11
ISBN (Electronic)3540230033, 9783540230038
DOIs
Publication statusPublished - 2004

Publication series

NameLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume3189
ISSN (Print)0302-9743
ISSN (Electronic)1611-3349

All Science Journal Classification (ASJC) codes

  • Theoretical Computer Science
  • Computer Science(all)

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  • Cite this

    Kim, B. U., Park, W. C., Yang, S. B., & Han, T. D. (2004). A cost-effective supersampling for full scene antialiasing. In P-C. Yew, & J. Xue (Eds.), Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (pp. 271-281). (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Vol. 3189). Springer Verlag. https://doi.org/10.1007/978-3-540-30102-8_23