Efficient implementation of higher order image interpolation

This work presents a new method of fast cubic and higher order image interpolation. The evaluation of the piecewise n-th order polynomial kernels is accelerated by transforming the polynomials into the interval [0, 1], which has the advantage that some terms of the polynomials disappear, and that several coefficients could be precalculated, which is proven in the paper. The results are exactly the same as using standard n-th order interpolation, but the computational complexity is reduced. Calculating the interpolation weights for the cubic convolution only needs about 60% of the time compared to the classical method optimized by the Horner’s rule. This allows a new efficient implementation for image interpolation.