EPFL | Biomedical Imaging Group | Interpolation Prefilter

GPU Prefilter for Accurate Cubic B-Spline Interpolation

D. Ruijters, P. Thévenaz

The Computer Journal, vol. 55, no. 1, pp. 15–20, January 2012.

Achieving accurate interpolation is an important requirement for many signal-processing applications. While nearest-neighbor and linear interpolation methods are popular due to their native GPU support, they unfortunately result in severe undesirable artifacts. Better interpolation methods are known but lack a native GPU support. Yet, a particularly attractive one is prefiltered cubic-spline interpolation. The signal it reconstructs from discrete samples has a much higher fidelity to the original data than what is achievable with nearest-neighbor and linear interpolation. At the same time, its computational load is moderate, provided a sequence of two operations is applied: first, prefilter the samples, and only then reconstruct the signal with the help of a B-spline basis. It has already been established in the literature that the reconstruction step can be implemented efficiently on a GPU. This article focuses on an efficient GPU implementation of the prefilter, on how to apply it to multidimensional samples (e.g. RGB color images), and on its performance aspects.

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AUTHOR="Ruijters, D. and Th{\'{e}}venaz, P.",
TITLE="{GPU} Prefilter for Accurate Cubic \mbox{{B}-Spline}
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JOURNAL="The Computer Journal",
YEAR="2012",
volume="55",
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pages="15--20",
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