An efficient new super resolution algorithm based on the suppression of ringing artifacts

A new super resolution algorithm is proposed which can provide bandwidth extension of noisy images in a small number of iterations and is potentially capable of real time operation. Attempts to restore band-limited images frequently introduce ringing artifacts. Methods designed to reduce this ringing often suppress sharp features in the scene. In images with a well-defined background intensity, super resolution techniques involving a positive constraint are effective in suppressing this ringing and providing a high degree of bandwidth extension. Problems arise, however, in a general image where no such well-defined background exists. The first stage of the algorithm reported here addresses these problems by computing an effective background. Features that need to be enhanced then exist as blurred deviations from this background. The background is computed from the first and second differentials of the image with respect to further blurring. It has been possible to suppress ringing artifacts, resulting in bandwidth extension, by comparing the calculated background with the known original blurred image. An iterative procedure based on Gerchberg's error energy reduction technique has produced good results. Computer calculations applied to both synthetic images and real millimetre wave images show that the algorithm is effective, efficient and largely immune to noise.