Error metrics for smart image refinement

Julian Amann, Matthäus G. Chajdas, Rüdigger Westermann

Research output: Contribution to journalArticlepeer-review

Abstract

Scanline rasterization is still the dominating approach in real-time rendering. For performance reasons, realtime ray tracing is only used in special applications. However, ray tracing computes better shadows, reflections, refractions, depth-of-field and various other visual effects, which are hard to achieve with a scanline rasterizer. A hybrid rendering approach benefits from the high performance of a rasterizer and the quality of a ray tracer. In this work, a GPU-based hybrid rasterization and ray tracing system that supports reflections, depth-of-field and shadows is introduced. The system estimates the quality improvement that a ray tracer could achieve in comparison to a rasterization based approach. Afterwards, regions of the rasterized image with a high estimated quality improvement index are refined by ray tracing.

Original languageEnglish
Pages (from-to)127-136
Number of pages10
JournalJournal of WSCG
Volume20
Issue number2
StatePublished - 2012

Keywords

  • Depth-of-field error metric
  • Hybrid rendering
  • Reflection error metric

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