A TGV-Based Framework for Variational Image Decompression, Zooming, and Reconstruction. Part II: Numerics

DOI10.1137/15M1023877zbMath1333.94007OpenAlexW4252755725WikidataQ57561952 ScholiaQ57561952MaRDI QIDQ2797763

Martin Holler, Kristian Bredies

Publication date: 31 March 2016

Published in: SIAM Journal on Imaging Sciences (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1137/15m1023877

zbMATH Keywords

image reconstructionprimal-dual algorithmtotal generalized variationJPEG 2000 decompressionJPEG decompressionvariational zooming

Mathematics Subject Classification ID

Ill-posedness and regularization problems in numerical linear algebra (65F22) Convex programming (90C25) Numerical methods involving duality (49M29) Image processing (compression, reconstruction, etc.) in information and communication theory (94A08)

Related Items (17)

Deep Learning--Based Dictionary Learning and Tomographic Image Reconstruction ⋮ A function space framework for structural total variation regularization with applications in inverse problems ⋮ Coupled regularization with multiple data discrepancies ⋮ Dualization and Automatic Distributed Parameter Selection of Total Generalized Variation via Bilevel Optimization ⋮ A sparsity regularization and total variation based computational framework for the inverse medium problem in scattering ⋮ Template-based CT reconstruction with optimal transport and total generalized variation ⋮ A new effective bias field correction model with TGV regularization ⋮ Compressive total variation for image reconstruction and restoration ⋮ Temporal Huber regularization for DCE-MRI ⋮ Higher-order total variation approaches and generalisations ⋮ An Algorithm for Second Order Mumford--Shah Models Based on a Taylor Jet Formulation ⋮ A convex variational model for learning convolutional image atoms from incomplete data ⋮ Total Generalized Variation for Manifold-Valued Data ⋮ A TGV-Based Framework for Variational Image Decompression, Zooming, and Reconstruction. Part I: Analytics ⋮ Regularization with multilevel non-stationary tight framelets for image restoration ⋮ Infimal Convolution of Oscillation Total Generalized Variation for the Recovery of Images with Structured Texture ⋮ Modern regularization methods for inverse problems

Uses Software

• CUDA
• FFTW

Cites Work

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• A TGV-Based Framework for Variational Image Decompression, Zooming, and Reconstruction. Part I: Analytics
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• A Primal–Dual Method for Total-Variation-Based Wavelet Domain Inpainting
• Total Generalized Variation
• Enhancement of JPEG-compressed images by re-application of JPEG

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