Artículos de revistas
Superiorization of incremental optimization algorithms for statistical tomographic image reconstruction
Fecha
2017-04-01Registro en:
Inverse Problems. Bristol: Iop Publishing Ltd, v. 33, n. 4, 26 p., 2017.
0266-5611
10.1088/1361-6420/33/4/044010
WOS:000395928000010
WOS000395928000010.pdf
Autor
Universidade Estadual Paulista (Unesp)
Fed Univ Technol
CNPEM
Institución
Resumen
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.