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C3S2E
2009
ACM

CPU, SMP and GPU implementations of Nohalo level 1, a fast co-convex antialiasing image resampler

9 years 1 months ago
CPU, SMP and GPU implementations of Nohalo level 1, a fast co-convex antialiasing image resampler
This article introduces Nohalo level 1 (“Nohalo”), the simplest member of a family of image resamplers which straighten diagonal interfaces without adding noticeable nonlinear artifacts. Nohalo is interpolatory, co-monotone, coconvex, antialiasing, local average preserving, continuous, and exact on linears. Like many edge-enhancing methods, Nohalo has two main stages: first, nonlinear interpolation is used to create a double-density version of the original image; this doubledensity image is then resampled with bilinear interpolation. Nohalo is especially suited for GPU computing because the nonlinear slopes can be computed once and stored in a low bit-depth texture without rounding error, because the final bilinear stage can be performed in hardware, and because monotonicity allows full use of the texture’s dynamic range. Demand-driven implementations for CPUs and SMPs are more complex, and require extra work to fix bottlenecks. Efficient implementations of the minmod functio...
Nicolas Robidoux, Minglun Gong, John Cupitt, Adam
Added 28 May 2010
Updated 28 May 2010
Type Conference
Year 2009
Where C3S2E
Authors Nicolas Robidoux, Minglun Gong, John Cupitt, Adam Turcotte, Kirk Martinez
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