Solving non-negative linear inverse problems with the NeAREst method

Published

Journal Article

This paper introduces the theoretical development of a numerical method, named NeAREst, for solving non-negative linear inverse problems, which arise often from physical or probabilistic models, especially, in image estimation with limited and indirect measurements. The Richardson-Lucy (RL) iteration is omnipresent in conventional methods that are based on probabilistic assumptions, arguments and techniques. Without resorting to probabilistic assumptions, NeAREst retains many appealing properties of the RL iteration by utilizing it as the substrate process and provides much needed mechanisms for acceleration as well as for selection of a target solution when many admissible ones exist.

Full Text

Duke Authors

Cited Authors

  • Sun, X; Pitsianis, NP

Published Date

  • December 17, 2008

Published In

Volume / Issue

  • 7074 /

International Standard Serial Number (ISSN)

  • 0277-786X

Digital Object Identifier (DOI)

  • 10.1117/12.795479

Citation Source

  • Scopus