Empirical evaluation of a bound on image superresolution performance

Images restored by linear shift-variant and nonlinear restoration techniques contain spectral energy beyond the optical system cutoff frequency. We have recently analyzed this aspect of image superresolution in terms of accurate extrapolation of the image spectrum. A closed-form expression for an approximate lower bound on extrapolation performance has been derived for continuous signals. In this paper, we present new empirical evidence in support of the derived bound. We then discuss performance for the discrete imaging case, including a discrete analogy to the analytic continuation theorem. Empirical results are presented which support our hypothesis that substantial bandwidth extrapolation is achievable for discrete images. Finally, we discuss potential applications of these results to the development of new restoration algorithms.