Superiorization of incremental optimization algorithms for statistical tomographic image reconstruction. (1st March 2017)

• Record Type: Journal Article
• Authors: Helou, E S; Zibetti, M V W; Miqueles, E X
• Is Part Of: Inverse problems. Volume 33:Number 4(2017:Apr.)
• Publication Date: 2017-03-01
• Subjects: superiorization -- convex optimization -- tomographic image reconstruction; Inverse problems (Differential equations) -- Periodicals; 515.357
• DOI: 10.1088/1361-6420/33/4/044010
• Languages: English
• ISSNs: 0266-5611

Abstract

Abstract: 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 superiorization schemes are evaluated. Theoretical analysis of the methods as well as computational experiments with both synthetic and real data are provided.