Total Variation Restoration of Images Corrupted by Poisson Noise with Iterated Conditional Expectations

DOI10.1007/978-3-319-18461-6_15zbMath1444.94003OpenAlexW795930426MaRDI QIDQ3300298

Tieyong Zeng, Rémy Abergel, Lionel Moisan, Cécile Louchet

Publication date: 28 July 2020

Published in: Lecture Notes in Computer Science (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1007/978-3-319-18461-6_15

zbMATH Keywords

total variationincomplete gamma functionposterior meanimage denoisingfixed-point algorithmstaircasing effectPoisson noise removalmarginal conditional mean

Mathematics Subject Classification ID

Image processing (compression, reconstruction, etc.) in information and communication theory (94A08)

Related Items (6)

Mixed noise removal framework using a nonlinear fourth-order PDE-based model ⋮ Hybrid regularized cone-beam reconstruction for axially symmetric object tomography ⋮ The Shannon total variation ⋮ A nonlocal low rank model for Poisson noise removal ⋮ Accelerated alternating minimization algorithm for Poisson noisy image recovery ⋮ A Total Variation Based Method for Multivariate Time Series Segmentation

Uses Software

• DLMF

Cites Work

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• Nonlinear total variation based noise removal algorithms
• Why least squares and maximum entropy? An axiomatic approach to inference for linear inverse problems
• A first-order primal-dual algorithm for convex problems with applications to imaging
• Image restoration with discrete constrained total variation. I: Fast and exact optimization
• Posterior Expectation of the Total Variation Model: Properties and Experiments
• Total Variation in Imaging
• A Review of Image Denoising Algorithms, with a New One

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