POCS: a uniform framework for iterative image reconstruction algorithms

TitlePOCS: a uniform framework for iterative image reconstruction algorithms
Publication TypeConference Paper
Year of Publication1995
AuthorsMailloux, G. E., R. Noumeir, and R. Lemieux
Conference NameElectrical and Computer Engineering, 1995. Canadian Conference on
Pagination937 -940 vol.2
Date Publishedsep.
Keywordsconvex constraints, Euclidian distance, image reconstruction, iterative image reconstruction algorithms, iterative methods, iterative reconstruction algorithms, noise, partial noisy data, POCS, projection onto convex sets, pseudodistances, relaxation parameters

The theory of projection onto convex sets (POCS) is very useful for comparing iterative reconstruction algorithms. Although originally developed with the Euclidian distance, it has been shown that POCS can be attended to pseudo-distances or can even use a different distance for each convex set. Five well known iterative algorithms that can be used to reconstruct images from partial noisy data have been formulated by POCS. Additional convex constraints and relaxation parameters can thus be introduced in these algorithms


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