GPU Prefilter for Accurate Cubic B-spline Interpolation

Daniel Ruijters, Philippe Thevenaz
iXR Innovation, Philips Healthcare, Best, the Netherlands
The Computer Journal, Vol.55, No.1, 2012


   title={GPU Prefilter for Accurate Cubic B-spline Interpolation},

   author={Ruijters, D. and Th{‘e}venaz, P.},

   journal={The Computer Journal},



   publisher={Br Computer Soc}


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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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