Paper
1 February 2006 Real-time antialiasing using adaptive directional filtering
Author Affiliations +
Proceedings Volume 6063, Real-Time Image Processing 2006; 606309 (2006) https://doi.org/10.1117/12.642153
Event: Electronic Imaging 2006, 2006, San Jose, California, United States
Abstract
In this paper we present an enhanced real-time selective antialiasing solution. We propose to use a directional filtering technique as an antialiasing tool. The best post-processing antialiasing effect will be obtained if we apply the low-pass filter along local orientation of antialiased features. Previously authors proposed a complicated curve fitting method as a solution for the local feature antialiasing. Here we propose a more simple and efficient solution. Instead of using a curve fitting method based on second order intensity derivatives, we can use directly a set of first order derivatives applied on the z-buffer content. For each feature direction detected an appropriate directional Gaussian convolution filter can be applied. This way the lowpass filter is applied along local features selected for antialiasing, filtering out high frequency distortions due to intermodulation. In this approach the high-pass convolution filtering applied on the zbuffer has a twofold application: it selects the objects edges that need to be antialiased and it gives a local feature direction allowing for edge reconstruction. The advantage of the approach proposed here is that it preserves texture details. Textures usually are filtered independently using trilinear or anisotropic filtering, which with traditional antialiasing techniques leads to overblurring.
© (2006) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.
Przemyslaw Rokita "Real-time antialiasing using adaptive directional filtering", Proc. SPIE 6063, Real-Time Image Processing 2006, 606309 (1 February 2006); https://doi.org/10.1117/12.642153
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KEYWORDS
Convolution

Linear filtering

Anisotropic filtering

Digital filtering

Image processing

Image filtering

Signal processing

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