Interleaved Sampling

  • The sampling of functions is one of the most fundamental tasks in computer graphics, and occurs in a variety of different forms. The known sampling methods can roughly be grouped in two categories. Sampling on regular grids is simple and efficient, and the algorithms are often easy to built into graphics hardware. On the down side, regular sampling is prone to aliasing artifacts that are expensive to overcome. Monte Carlo methods, on the other hand, mask the aliasing artifacts by noise. However due to the lack of coherence, these methods are more expensive and not weil suited for hardware implementations. In this paper, we introduce a novel sampling scheme where samples from several regular grids are a combined into a single irregular sampling pattern. The relative positions of the regular grids are themselves determined by Monte Carlo methods. This generalization obtained by interleaving yields,significantly improved quality compared to traditional approaches while at the same time preserving much of the advantageous coherency of regular sampling. We demonstrate the quality of the new sampling scheme with a number of applications ranging from supersampling over motion blur simulation to volume rendering. Due to the coherence in the interleaved samples, the method is optimally suited for implementations in graphics hardware.

Volltext Dateien herunterladen

Metadaten exportieren

Weitere Dienste

Teilen auf Twitter Suche bei Google Scholar
Verfasserangaben:Alexander Keller, Wolfgang Heidrich
URN (Permalink):urn:nbn:de:hbz:386-kluedo-49666
Schriftenreihe (Bandnummer):Interner Bericht des Fachbereich Informatik (308)
Sprache der Veröffentlichung:Englisch
Veröffentlichungsdatum (online):26.10.2017
Jahr der Veröffentlichung:2001
Veröffentlichende Institution:Technische Universität Kaiserslautern
Datum der Publikation (Server):26.10.2017
Fachbereiche / Organisatorische Einheiten:Fachbereich Informatik
DDC-Sachgruppen:0 Allgemeines, Informatik, Informationswissenschaft / 004 Informatik
Lizenz (Deutsch):Creative Commons 4.0 - Namensnennung, nicht kommerziell, keine Bearbeitung (CC BY-NC-ND 4.0)