Improved POCS-based image reconstruction from irregularly-spaced samples

This paper presents an enhanced POCS-based (projection onto convex sets) method for the reconstruction of a regularly-sampled image from its irregularly-spaced samples. Such a reconstruction is often needed in image processing and coding, for example when using motion compensation. The proposed approach applies two operators sequentially: bandwidth limitation and sample substitution, and is based on our earlier work. The contribution of this paper is a new, simpler implementation of the algorithm that allows for faster convergence, and provides better performance, although at the cost of increased memory requirements.