EWA Splatting

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EWA Splatting

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Title: EWA Splatting
Author: Zwicker, Matthias; Pfister, Hanspeter; van Baar, Jeroen; Gross, Markus

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Citation: Zwicker, Matthias, Hanspeter Pfister, Jeroen van Baar, and Markus Gross. 2002. EWA Splatting. IEEE Transactions on Visualization and Computer Graphics 8(3): 223-238.
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Abstract: In this paper, we present a framework for high quality splatting based on elliptical Gaussian kernels. To avoid aliasing artifacts, we introduce the concept of a resampling filter, combining a reconstruction kernel with a low-pass filter. Because of the similarity to Heckbert's EWA (elliptical weighted average) filter for texture mapping, we call our technique EWA splatting. Our framework allows us to derive EWA splat primitives for volume data and for point-sampled surface data. It provides high image quality without aliasing artifacts or excessive blurring for volume data and, additionally, features anisotropic texture filtering for point-sampled surfaces. It also handles nonspherical volume kernels efficiently; hence, it is suitable for regular, rectilinear, and irregular volume datasets. Moreover, our framework introduces a novel approach to compute the footprint function, facilitating efficient perspective projection of arbitrary elliptical kernels at very little additional cost. Finally, we show that EWA volume reconstruction kernels can be reduced to surface reconstruction kernels. This makes our splat primitive universal in rendering surface and volume data.
Published Version: doi:10.1109/TVCG.2002.1021576
Other Sources: http://gvi.seas.harvard.edu/sites/all/files/VIS2001_1.pdf
Terms of Use: This article is made available under the terms and conditions applicable to Other Posted Material, as set forth at http://nrs.harvard.edu/urn-3:HUL.InstRepos:dash.current.terms-of-use#LAA
Citable link to this page: http://nrs.harvard.edu/urn-3:HUL.InstRepos:4138240
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