An Iterative Method for Edge-Preserving MAP Estimation When Data-Noise Is Poisson

DOI10.1137/080726884zbMath1215.65116OpenAlexW2009688996MaRDI QIDQ3079324

John Goldes, Johnathan M. Bardsley

Publication date: 2 March 2011

Published in: SIAM Journal on Scientific Computing (Search for Journal in Brave)

Full work available at URL: https://semanticscholar.org/paper/b706a95f09910e6c5d23e0561e4993ddb71ddc0c

zbMATH Keywords

global convergencenumerical examplesinverse problemsedge-preserving regularizationBayesian statistical methodsnonnegatively constrained optimizationPoisson likelihood function

Mathematics Subject Classification ID

Numerical optimization and variational techniques (65K10) Existence of optimal solutions to problems involving randomness (49J55)

Related Items

An MCMC method for uncertainty quantification in nonnegativity constrained inverse problems ⋮ Primal-dual algorithms for total variation based image restoration under Poisson noise ⋮ A fast algorithm for deconvolution and Poisson noise removal ⋮ Regularization parameter selection and an efficient algorithm for total variation-regularized positron emission tomography

Uses Software

• KELLEY