Locally adaptive total variation for removing mixed Gaussian–impulse noise

DOI10.1080/00207160.2018.1438603zbMath1499.94011OpenAlexW2794068718MaRDI QIDQ5031781

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Publication date: 16 February 2022

Published in: International Journal of Computer Mathematics (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1080/00207160.2018.1438603

zbMATH Keywords

total variation minimizationautomated parameter selectionlocally dependent regularization parametermixed Gaussian-impulse noisecombined \(L^1/L^2\) data fidelity

Mathematics Subject Classification ID

Numerical optimization and variational techniques (65K10) Computing methodologies for image processing (68U10) Image processing (compression, reconstruction, etc.) in information and communication theory (94A08)

Related Items (4)

A spatially adaptive hybrid total variation model for image restoration under Gaussian plus impulse noise ⋮ A primal-dual finite element method for scalar and vectorial total variation minimization ⋮ Overlapping Domain Decomposition Methods for Total Variation Denoising ⋮ Diffusion based method for impulse noise removal using residual feedback

Uses Software

• DUNE-ACFem

Cites Work

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