Tomographic reconstruction of 3D objects using marked point process framework

DOI10.1007/s10851-018-0800-6zbMath1436.62301OpenAlexW2790173029WikidataQ130168545 ScholiaQ130168545MaRDI QIDQ1799592

Lionel Thomas, Olivier Alata, Riadh Ben~Salah, Laurent David, Benoit Tremblais

Publication date: 19 October 2018

Published in: Journal of Mathematical Imaging and Vision (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1007/s10851-018-0800-6

zbMATH Keywords

simulated annealingstochastic modelsmarked point processes3D object reconstructionMetropolis-Hastings-Green (MHG) algorithmtomographic PIV

Mathematics Subject Classification ID

Image analysis in multivariate analysis (62H35) Image processing (compression, reconstruction, etc.) in information and communication theory (94A08) Point processes (e.g., Poisson, Cox, Hawkes processes) (60G55)

Uses Software

• SLIP

Cites Work

• Reversible jump Markov chain Monte Carlo computation and Bayesian model determination
• Counting the faces of randomly-projected hypercubes and orthants, with applications
• Block‐iterative algorithms
• Stochastic Relaxation, Gibbs Distributions, and the Bayesian Restoration of Images
• Markov Point Processes and Their Applications
• An Introduction to the Theory of Point Processes
• A Marked Point Process for Modeling Lidar Waveforms
• Generalized Iterative Scaling for Log-Linear Models
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