SUPERRESOLUTION OF IMAGES - ALGORITHMS, PRINCIPLES, PERFORMANCE

A new facet of image restoration research has begun to emerge in recen t years: super-resolution of images, which we define as the processing of an image so as to recover object information from beyond the spati al frequency bandwidth of the optical system that formed the image. Si mple Fourier analysis would indicate that superresolution is not possi ble. Therefore, it is important to reconcile this simplistic view with the existing algorithms that have been demonstrated to achieve super- resolution. In this article, we consider some of the algorithms that h ave demonstrated super-resolution and discuss the common principles th at they share which makes it possible for them to recover some of the lost bandwidth of the object. We also consider the question of super-r esolution performance, which is the measure of how much lost bandwidth can be recovered from a super-resolution algorithm, and how the perfo rmance is related to the algorithm principles that allow super-resolut ion to occur. We conclude with examples of super-resolution. (C) 1995 John Wiley & Sons, Inc.