TY - JOUR
T1 - GPU prefilter for accurate cubic B-spline interpolation
AU - Ruijters, Daniel
AU - Thévenaz, Philippe
PY - 2012/1
Y1 - 2012/1
N2 - 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.
AB - 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.
KW - B-spline
KW - cubic interpolation
KW - GPU acceleration
UR - http://www.scopus.com/inward/record.url?scp=84555186783&partnerID=8YFLogxK
U2 - 10.1093/comjnl/bxq086
DO - 10.1093/comjnl/bxq086
M3 - Article
SN - 0010-4620
VL - 55
SP - 15
EP - 20
JO - The Computer Journal
JF - The Computer Journal
IS - 1
ER -