Superiorization of incremental optimization algorithms for statistical tomographic image reconstruction
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Data
2017-04-01
Autores
Helou, E. S. [UNESP]
Zibetti, M. V. W.
Miqueles, E. X.
Título da Revista
ISSN da Revista
Título de Volume
Editor
Iop Publishing Ltd
Resumo
We propose the superiorization of incremental algorithms for tomographic image reconstruction. The resulting methods follow a better path in its way to finding the optimal solution for the maximum likelihood problem in the sense that they are closer to the Pareto optimal curve than the non-superiorized techniques. A new scaled gradient iteration is proposed and three super-iorization schemes are evaluated. Theoretical analysis of the methods as well as computational experiments with both synthetic and real data are provided.
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Palavras-chave
superiorization, convex optimization, tomographic image reconstruction
Como citar
Inverse Problems. Bristol: Iop Publishing Ltd, v. 33, n. 4, 26 p., 2017.