Principles of Interpolator Design and Evaluation
Abstract
It is shown that an error spectrum can be used to describe the performance of any convolutional interpolator operating on equally spaced points from an over sampled image. The error spectrum is linear in the image power spectrum and in an error factor that depends on only the interpolator and the distance from the sample points. The same form is shown to describe the interpolation of undersampled data, in an average sense. Simple forms are given for the error factor in either Fourier or real space, and standard interpolators are evaluated with them. Optimal interpolators are derived for various model image spectra: constant, Lorentzian, power law, and Gaussian. Practical methods of interpolator design are devised for use with image spectra that are known only partially or are not easily characterized analytically.
Document Details
- Document Type
- Technical Report
- Publication Date
- Nov 15, 1991
- Accession Number
- ADA242822
Entities
People
- Alan Schaum
Organizations
- United States Naval Research Laboratory