Iterative image reconstruction algorithms based on the theory of convex projections

Five iterative algorithms to reconstruct images From partial noisy data have been formulated and compared by using the theory of projection onto convex sets (POCS). This formulation clearly shows the dependence on the initial solution, allows the introduction of a prior distribution in the distance to be minimized and the use of additional convex constraints