An optimized cubic interpolator for image resampling

Abstract

It is noted that the cubic resampling function is only one member of a family of functions, defined by the single parameter of the slope of the cubic function at its first zero crossing, whose other members are in some cases superior to the standard cubic. This superiority is especially noteworthy with respect to the extent of gray level overshoot induced by the resampling process at high contrast edges. It is shown that there is an optimum member of this 'parametric cubic convolution' family which minimizes the mean-squared radiometric error arising from interpolation. This interpolator requires no additional computation time over the conventional cubic one. These conclusions are supported and illustrated by resampling simulations with both a high resolution digitized aerial image and a Landsat Multispectral Scanner image.