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Footprint Area Sampled Texturing

  • University of Minnesota Twin Cities
  • Stony Brook University

Research output: Contribution to journalArticlepeer-review

8 Scopus citations

Abstract

We study texture projection based on a four region subdivision: magnification, minification, and two mixed regions. We propose improved versions of existing techniques by providing exact filtering methods which reduce both aliasing and overblurring, especially in the mixed regions. We further present a novel texture mapping algorithm called FAST (Footprint Area Sampled Texturing), which not only delivers high quality, but also is efficient. By utilizing coherence between neighboring pixels, performing prefiltering, and applying an area sampling scheme, we guarantee a minimum number of samples sufficient for effective antialiasing. Unlike existing methods (e.g., MIP-map, Feline), our method adapts the sampling rate in each chosen MIP-map level separately to avoid undersampling in the lower level l for effective antialiasing and to avoid oversampling in the higher level l + 1 for efficiency. Our method has been shown to deliver superior image quality to Feline and other methods while retaining the same efficiency. We also provide implementation trade offs to apply a variable degree of accuracy versus speed.

Original languageEnglish
Pages (from-to)230-240
Number of pages11
JournalIEEE Transactions on Visualization and Computer Graphics
Volume10
Issue number2
DOIs
StatePublished - Mar 2004

Keywords

  • Anisotropic filtering
  • Antialiasing
  • Backward mapping
  • Footprint area sampling
  • Forward mapping
  • Hardware
  • Texture mapping

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