Solving Non-negative Linear Inverse Problems with the NeAREst Method

@inproceedings{Sun2008SolvingNL,
  title={Solving Non-negative Linear Inverse Problems with the NeAREst Method},
  author={Xiaobai Sun and Nikos Pitsianis},
  year={2008}
}
This paper introduces the theoretical development of a numerical method, named NeAREst, for solving nonnegative 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… CONTINUE READING

References

Publications referenced by this paper.
Showing 1-10 of 13 references

From image deblurring to optimal investment: Maximum likelihood solutions for positive linear inverse problems

  • Y. Vardi, D. Lee
  • J. R. Statist. Soc. B. 55(3), 569–612 (1993).
  • 1993

Why least squares and maximum entropy? an axiomatic approach to inference for linear inverse problems

  • I. Csiszár
  • Anal. Stat. 19(4), 2032–2066 (1991).
  • 1991

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