An analysis of regularization by diffusion for ill-posed Poisson likelihood estimations

DOI10.1080/17415970802231594zbMath1167.65074OpenAlexW2092917290MaRDI QIDQ3630083

Johnathan M. Bardsley, N'Djekornom Laobeul

Publication date: 2 June 2009

Published in: Inverse Problems in Science and Engineering (Search for Journal in Brave)

Full work available at URL: http://www.informaworld.com/smpp/./content~db=all~content=a906850434

zbMATH Keywords

optimizationregularizationlinear ill-posed problemscompact integral operatorsPoisson likelihood estimation

Mathematics Subject Classification ID

Integral operators (45P05) Numerical methods for ill-posed problems for integral equations (65R30) Linear integral equations (45A05)

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Cites Work

• An efficient computational method for total variation-penalized Poisson likelihood estimation
• Regularization with differential operators. I: General theory
• A Gaussian hypermodel to recover blocky objects
• Inverse problems with structural prior information
• A Nonnegatively Constrained Convex Programming Method for Image Reconstruction
• Computational Methods for Inverse Problems
• Tikhonov regularized Poisson likelihood estimation: theoretical justification and a computational method
• Covariance-Preconditioned Iterative Methods for Nonnegatively Constrained Astronomical Imaging
• Letter to the Editor—On the Convexity of Quadratic Forms Over Convex Sets

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