  In constraining iterative processes, the algorithmic operator of the
iterative process is pre-multiplied by a constraining operator at each
iterative step. This enables the constrained algorithm, besides solving the
original problem, also to find a solution that incorporates some prior
knowledge about the solution. This approach has been useful in image
restoration and other image processing situations when a single constraining
operator was used. In the field of image reconstruction from projections a
priori information about the original image, such as smoothness or that it
belongs to a certain closed convex set, may be used to improve the
reconstruction quality. We study here constraining of iterative processes by a
family of operators rather than by a single operator.
