2010 Sixth International Conference on Signal-Image Technology and Internet Based Systems (2010)
Kuala Lumput, Malaysia
Dec. 15, 2010 to Dec. 18, 2010
DOI Bookmark: http://doi.ieeecomputersociety.org/10.1109/SITIS.2010.31
Rasterization algorithms fall into two main categories, point-sampling and area-sampling. Point-sampling techniques allow for high quality reconstruction, but suffer from aliasing artifacts, time-costly to attenuate. On the other side, area-sampling, popularized by Edwin C. Catmull's Unweighted Area Sampling or UAS, is equivalent to point-sampling at an infinite rate, but reconstruction is restricted to a unit-size box-filter, which offers very poor reconstruction characteristics. We propose a new rasterization algorithm named multiresolution integration, MI which provides high quality reconstruction such as point sampling techniques may do, while achieving speed in the range of unweighted area sampling: a weighted average of box filters is used to approximate the convolution integral between the polygon and any kernel of finite extents. A simple and fast implementation is described, providing high quality 2D rasterization at interactive speed. Examples and benchmarks demonstrate both the quality and speed of this new method.
rasterization, anti-aliasing, convolution, multi-resolution integration
V. Boyer and R. Lemoine, "Rasterization by Multiresolution Integration," 2010 Sixth International Conference on Signal-Image Technology and Internet Based Systems(SITIS), Kuala Lumput, Malaysia, 2010, pp. 127-133.