Non-Sampled Anti-Aliasing (English)

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In this paper we present a parallel method for high-quality edge anti-aliasing in rasterization. In contrast to traditional graphics hardware methods, which rely on massive oversampling to combat aliasing issues, we evaluate a closed-form solution of the associated prefilter convolution. This enables the use of a wide range of filter functions with arbitrary kernel sizes, as well as general shading methods such as texture mapping or complex illumination models. Due to the use of analytic solutions, our results are exact in the mathematical sense and provide objective ground-truth for other anti-aliasing methods and enable the rigorous comparison of different models and filters. An efficient implementation on general purpose graphics hardware is discussed and several comparisons to existing techniques and of various filter functions are given.

Table of contents conference proceedings

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Transfusive Weights for Content-Aware Image Manipulation
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Datasets and Benchmarks for Densely Sampled 4D Light Fields
Wanner, Sven / Meister, Stephan / Goldluecke, Bastian | 2013
Sampled and Analytic Rasterization
Auzinger, Thomas / Wimmer, Michael | 2013
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Integrated Multi-aspect Visualization of 3D Fluid Flows
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Adaptive Surface Visualization of Vessels with Embedded Blood Flow Based on the Suggestive Contour Measure
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A Semi-Automated Method for Subject-Specific Modeling of the Spinal Canal from Computed Tomography Images and Dynamic Radiographs
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Progressive Visibility Caching for Fast Indirect Illumination
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