On the comparison of interpolation methods 论文

1988IEEE Transactions on Medical Imaging引用 257
Image and Signal Denoising MethodsIterative Methods for Nonlinear EquationsAdvanced Numerical Analysis Techniques

摘要

A study of different cubic interpolation kernels in the frequency domain is presented that reveals novel aspects of both cubic spline and cubic convolution interpolation. The kernel used in cubic convolution is of finite support and depends on a parameter to be chosen at will. At the Nyquist frequency, the spectrum attains a value that is independent of this parameter. Exactly the same value is found at the Nyquist frequency in the cubic spline interpolation. If a strictly positive interpolation kernel is of importance in applications, cubic convolution with the parameter value zero is recommended.