Adaptive Supersampling
for Deferred Anti-Aliasing

Authors: Matthias Holländer
Telecom ParisTech - CNRS/LTCI

Tamy Boubekeur
Telecom ParisTech - CNRS/LTCI

Elmar Eisemann
Delft University of Technology

Editor: John Hable, 19lights
Editor-in-Chief: Morgan McGuire, Williams College &
NVIDIA

Abstract

We present a novel approach to perform anti-aliasing in a deferred-rendering context. Our approach is based on supersampling; the scene is rasterized into an enlarged geometry buffer, i.e., each pixel of the final image corresponds to a window of attributes within this buffer. For the final image, we sample this window adaptively based on different metrics accounting for geometry and appearance to derive the pixel shading. Further, we use anisotropic filtering to avoid texturing artifacts. Our approach concentrates the workload where needed and allows faster shading in various supersampling scenarios, especially when the shading cost per pixel is high.

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Citation: M. Holländer, T. Boubekeur, and E. Eisemann, Adaptive Supersampling for Deferred Anti-Aliasing, Journal of Computer Graphics Techniques (JCGT), vol. 2, no. 1, 1-14, 02 Mar. 2013. Available online http://jcgt.org/published/0002/01/01/

Copyright: © 2013 Holländer, Boubekeur, and Eisemann

Received: 2012-09-05; Recommended: 2012-11-20; Published: 2013-03-02