Improving digital signal interpolation: L2-optimal kernels with kernel-invariant interpolation speed

Interpolation is responsible for digital signal resampling and can significantly degrade the original signal quality if not done properly. For many years, optimal interpolation algorithms were sought within constrained classes of interpolation kernel functions. We derive a new family of unconstrained L2-optimal interpolation kernels, and compare their properties to the previously known. Although digital images are used to illustrate this work, our L2-optimal kernels can be applied to interpolate any digital signals.

Bilateral filters: what they can and cannot do

Nonlinear bilateral filters (BF) deliver a fine blend of computational simplicity and blur-free denoising. However, little is known about their nature, noise-suppressing properties, and optimal choices of filter parameters. Our study is meant to fill this gap-explaining the underlying mechanism of bilateral filtering and providing the methodology for optimal filter selection. Practical application to CT image denoising is discussed to illustrate our results.