Interpolation of remote sensing imagery is a ubiquitous task, required for myriad purposes such as registration of multiple frames, correction of geometric distortions, and mitigation of platform vibration distortions in imagery. Interpolation is also a classically systemic task, in that interpolator performance in pixel placement, anti-aliasing, and blur, affects the design of other system components, notably reconstruction filters. Interpolator design in a system context is the problem which first motivated development of the latent and apparent image quality metrics previously presented at Visual Information Processing XI and XIII.
This paper presents a suite of common interpolator design philosophies with length-4 examples of the designs analyzed in terms of signal processing and image quality metrics. Conclusions are drawn both with respect to the designs and with respect to the metrics.