Amortized supersampling

  • Authors:
  • Lei Yang;Diego Nehab;Pedro V. Sander;Pitchaya Sitthi-amorn;Jason Lawrence;Hugues Hoppe

  • Affiliations:
  • Hong Kong UST;Microsoft Research;Hong Kong UST;University of Virginia;University of Virginia;Microsoft Research

  • Venue:
  • ACM SIGGRAPH Asia 2009 papers
  • Year:
  • 2009

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Abstract

We present a real-time rendering scheme that reuses shading samples from earlier time frames to achieve practical antialiasing of procedural shaders. Using a reprojection strategy, we maintain several sets of shading estimates at subpixel precision, and incrementally update these such that for most pixels only one new shaded sample is evaluated per frame. The key difficulty is to prevent accumulated blurring during successive reprojections. We present a theoretical analysis of the blur introduced by reprojection methods. Based on this analysis, we introduce a nonuniform spatial filter, an adaptive recursive temporal filter, and a principled scheme for locally estimating the spatial blur. Our scheme is appropriate for antialiasing shading attributes that vary slowly over time. It works in a single rendering pass on commodity graphics hardware, and offers results that surpass 4x4 stratified supersampling in quality, at a fraction of the cost.