An iterative method for restoring noisy blurred images

DOI10.1007/BF01599212zbMath0542.93068OpenAlexW1892183043MaRDI QIDQ795792

N. E. Zubov

Publication date: 1984

Published in: Circuits, Systems, and Signal Processing (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1007/bf01599212

zbMATH Keywords

innovationiterative image restorationnoisy blurred imagesnoncausal image model

Mathematics Subject Classification ID

Inference from stochastic processes and prediction (62M20) Time series, auto-correlation, regression, etc. in statistics (GARCH) (62M10) Estimation and detection in stochastic control theory (93E10) Identification in stochastic control theory (93E12)

Related Items (1)

Generalized maximum a posteriori processing of multichannel images and applications

Cites Work

• Unnamed Item
• Unnamed Item
• Partial differential equations and finite-difference methods in image processing. I: Image representation
• Estimation and identification of two-dimensional images
• Convergence criteria for iterative restoration methods
• Restoration of Noisy Images Using a Two-Dimensional Linear Model
• Two-dimensional discrete Markovian fields

This page was built for publication: An iterative method for restoring noisy blurred images