The DOI matches its Crossref record; 3 of the 3 references it cites were found in a registry or an index.
Image reconstruction and restoration: overview of common estimation structures and problems
Abstract
Developments in the theory of image reconstruction and restoration over the past 20 or 30 years are outlined. Particular attention is paid to common estimation structures and to practical problems not properly solved yet. The problem of image reconstruction and restoration is first formulated. Some of the current regularization approaches used to solve the problem are then described. The concepts of a priori information and compound criterion are introduced. A Bayesian interpretation of the regularization techniques is given which clarifies the role of the tuning parameters and indicates how they could be estimated. The practical aspects of computing the solution, first when the hyperparameters are known and second when they must be estimated, are then considered. Conclusions are drawn, and points that still need to be investigated are outlined.>
Overview
The claims and statistics of this paper haven’t been checked yet.
Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.
Integrity signals
Registry
Cites
Statistics
Verification
Claims the paper makes
The claims and statistics of this paper haven’t been checked yet.
Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.
Self-check
Percentages, sums and reported differences re-computed from the paper’s own numbers.
The self-check needs the paper’s full text.
Citations
Cites
Maximum Likelihood from Incomplete Data Via the EM Algorithm
Dempster, A. P., Laird, N. M., & Rubin, D. B. (1977) · Journal of the Royal Statistical Society Series B: Statistical Methodology · doi:10.1111/j.2517-6161.1977.tb01600.x · Cited by 50,444
Equation of State Calculations by Fast Computing Machines
Metropolis, N., Rosenbluth, A. W., Rosenbluth, M. N., Teller, A. H., & Teller, E. (1953) · The Journal of Chemical Physics · doi:10.1063/1.1699114 · Cited by 37,192
Principles of Computerized Tomographic Imaging
Kak, A. C., & Slaney, M. (2001) · doi:10.1137/1.9780898719277 · Cited by 5,809
Cited by
A New Alternating Minimization Algorithm for Total Variation Image Reconstruction
Wang, Y., Yang, J., Yin, W., & Zhang, Y. (2008) · SIAM Journal on Imaging Sciences · doi:10.1137/080724265 · Cited by 1,975
Deterministic edge-preserving regularization in computed imaging
Charbonnier, P., Blanc-Feraud, L., Aubert, G., & Barlaud, M. (1997) · IEEE Transactions on Image Processing · doi:10.1109/83.551699 · Cited by 1,301
Robust Solutions to Least-Squares Problems with Uncertain Data
El Ghaoui, L., & Lebret, H. (1997) · SIAM Journal on Matrix Analysis and Applications · doi:10.1137/s0895479896298130 · Cited by 1,076
Nonlinear image recovery with half-quadratic regularization
Geman, D., & Yang, C. (1995) · IEEE Transactions on Image Processing · doi:10.1109/83.392335 · Cited by 1,000
MEG: An Introduction to Methods
(2010) · Oxford University Press eBooks · doi:10.1093/acprof:oso/9780195307238.001.0001 · Cited by 408
Metadata
- Authors
- Demoment, G.
- Venue
- IEEE Transactions on Acoustics, Speech, and Signal Processing
- Published
- 1989
- Volume
- 37
- Issue
- 12
- Pages
- 2024-2036
- ISSN
- 0096-3518 (ISSN-L)
- OpenAlex
- W2151514667
- Cited by
- 647
- References
- 3
- FWCI
- 13.10
- Type
- journal article
- Language
- en
- Open access
- closed
About these checks
Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.
Statistics and arithmetic are recomputed, not judged.
Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.
What counts as a claim ›How we measure confidence ›How we check this ›
Are you an author, or do you see a problem with this page? Request a review
How to cite
Cite CoChat for the checks on this page, and the paper for its own findings.
- This page
- CoChat. (2026). Citation check: Image reconstruction and restoration: overview of common estimation structures and problems. https://app.cochat.ai/papers/10.1109/29.45551
- The paper
- Demoment, G. (1989). Image reconstruction and restoration: overview of common estimation structures and problems. IEEE Transactions on Acoustics, Speech, and Signal Processing. https://doi.org/10.1109/29.45551
Data sources
Bibliographic data: Semantic Scholar, OpenAlex, Crossref.
Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).
Semantic Scholar’s data is described in: Kinney, R., et al. (2023). The Semantic Scholar Open Data Platform. arXiv:2301.10140.
