A Robust Inversion Method According to a New Notion of Regularization for Poisson Data with an Application to Nanoparticle Volume Determination

DOI10.1137/15M1024354zbMath1382.78009OpenAlexW2259897490MaRDI QIDQ2789361

Federico Benvenuto, Houssem Haddar, Blandine Lantz

Publication date: 29 February 2016

Published in: SIAM Journal on Applied Mathematics (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1137/15m1024354

zbMATH Keywords

expectation maximizationPoisson datananoparticle volume determinationPoisson-like regularizationsmall angle X-ray scattering

Mathematics Subject Classification ID

Related Items (2)

A Study on Regularization for Discrete Inverse Problems with Model-Dependent Noise ⋮ Predictive risk estimation for the expectation maximization algorithm with Poisson data

Uses Software

• pyFAI

Cites Work

• Inverse acoustic and electromagnetic scattering theory.
• Regularization parameter selection methods for ill-posed Poisson maximum likelihood estimation
• Inverse diffraction for the Atmospheric Imaging Assembly in the Solar Dynamics Observatory
• On properties of the iterative maximum likelihood reconstruction method
• Regularization of multiplicative iterative algorithms with nonnegative constraint
• The expectation-maximization algorithm for ill-posed integral equations: a convergence analysis
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