Constrained image recovery in a product space

Authors:
P. L. Combettes
Affiliations:
-
Venue:
ICIP '95 Proceedings of the 1995 International Conference on Image Processing (Vol.2)-Volume 2 - Volume 2
Year:
1995

Citing 2
Cited 2

On some optimization techniques in image reconstruction from projections

Applied Numerical Mathematics - Applications of optimization
On Projection Algorithms for Solving Convex Feasibility Problems

SIAM Review

New iterative scheme with nonexpansive mappings for equilibrium problems and variational inequality problems in Hilbert spaces

Journal of Computational and Applied Mathematics
Strong convergence of a general iterative algorithm for equilibrium problems and variational inequality problems

Mathematical and Computer Modelling: An International Journal

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Abstract

In image recovery a priori knowledge and the observed data give rise to constraints on the solutions. In general, the recovery problem can be posed as that of minimizing a pertinent cost function over the resulting feasibility set. In this paper we present a product space framework for solving such problems, which leads to simplified formulations and to efficient parallel algorithms. Feasibility problems, quadratic minimization problems, and convex minimization problems are discussed.