Directional mean curvature for textured image demixing

DOI10.1016/j.apm.2021.10.006zbMath1525.94018arXiv1611.08625OpenAlexW3207765291MaRDI QIDQ6135658

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Publication date: 25 August 2023

Published in: Applied Mathematical Modelling (Search for Journal in Brave)

Full work available at URL: https://arxiv.org/abs/1611.08625

zbMATH Keywords

variational calculusfeature extractionmean curvaturesampling theorymultiscale analysisimage deblurringhigh-order PDEdemixing problemharmonic analsysis

Mathematics Subject Classification ID

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

Cites Work

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• Nonlinear total variation based noise removal algorithms
• A Fast Iterative Shrinkage-Thresholding Algorithm for Linear Inverse Problems
• ADI splitting schemes for a fourth-order nonlinear partial differential equation from image processing
• Image segmentation using Euler's elastica as the regularization
• Operator splittings, Bregman methods and frame shrinkage in image processing
• Augmented Lagrangian method for generalized TV-Stokes model
• Modeling oscillatory components with the homogeneous spaces \({B\dot MO}^{-\alpha}\) and \(\dot W^{-\alpha,p}\)
• Shearlets. Multiscale analysis for multivariate data.
• Modeling textures with total variation minimization and oscillating patterns in image processing
• Models for stationary max-stable random fields
• An algorithm for total variation minimization and applications
• Completely convex formulation of the Chan-Vese image segmentation model
• A combined first and second order variational approach for image reconstruction
• Multiphase segmentation for simultaneously homogeneous and textural images
• Image decompositions using bounded variation and generalized homogeneous Besov spaces
• Augmented Lagrangian method for a mean curvature based image denoising model
• Extreme value analysis of empirical frame coefficients and implications for denoising by soft-thresholding
• The Dantzig selector: statistical estimation when \(p\) is much larger than \(n\). (With discussions and rejoinder).
• Dual norms and image decomposition models
• 2D Empirical Transforms. Wavelets, Ridgelets, and Curvelets Revisited
• Image Denoising Using Mean Curvature of Image Surface
• A Fast Algorithm for Euler's Elastica Model Using Augmented Lagrangian Method
• Optimal approximations by piecewise smooth functions and associated variational problems
• The Split Bregman Method for L1-Regularized Problems
• Algorithms for Finding Global Minimizers of Image Segmentation and Denoising Models
• A binary level set model and some applications to Mumford-Shah image segmentation
• Noise removal using fourth-order partial differential equation with applications to medical magnetic resonance images in space and time
• Augmented Lagrangian Method, Dual Methods, and Split Bregman Iteration for ROF, Vectorial TV, and High Order Models
• A Variational Method in Image Recovery
• Active contours without edges
• New tight frames of curvelets and optimal representations of objects with piecewise C² singularities
• High-Order Total Variation-Based Image Restoration
• From differential equations to the construction of new wavelet-like bases
• Cartoon-Texture Image Decomposition Using Blockwise Low-Rank Texture Characterization
• Separation Surfaces in the Spectral TV Domain for Texture Decomposition
• Spectral Total-Variation Local Scale Signatures for Image Manipulation and Fusion
• Sampling-50 years after Shannon
• An iterative thresholding algorithm for linear inverse problems with a sparsity constraint
• Deep Convolutional Framelets: A General Deep Learning Framework for Inverse Problems
• Multiscale Texture Separation
• Cartoon-Texture Image Decomposition using Orientation Characteristics in Patch Recurrence
• A Total Variation Spectral Framework for Scale and Texture Analysis
• Structure-Texture Image Decomposition Using Deep Variational Priors
• A Tale of Two Bases: Local-Nonlocal Regularization on Image Patches with Convolution Framelets
• Image restoration: Total variation, wavelet frames, and beyond
• A Shearlet Approach to Edge Analysis and Detection
• Multiresolution Monogenic Signal Analysis Using the Riesz–Laplace Wavelet Transform
• Wavelet Steerability and the Higher-Order Riesz Transform
• Steerable Pyramids and Tight Wavelet Frames in $L_{2}({\BBR}^{d})$
• A Direct Approach Toward Global Minimization for Multiphase Labeling and Segmentation Problems
• Image Decomposition Using Total Variation and div(BMO)
• Fast Discrete Curvelet Transforms