Image restoration from degraded observations and from properties that
the image is supposed to satisfy has been approached by the method of
projections onto convex constraint sets. Previous attempts have incorp
orated only partially the knowledge that we possess about the image to
be restored because of difficulties in the implementation of some of
the projections. In the parallel-projection algorithm presented here t
he a priori knowledge can be fully exploited. Moreover, the algorithm
operates well even if the constraints are nonconvex and/or if the cons
traints have an empty intersection, without a limitation on the (finit
e) number of constraint sets.