Introduction to variational image-processing models and applications

DOI10.1080/00207160.2012.757073zbMath1278.68329OpenAlexW1997123714MaRDI QIDQ2868152

Ke Chen

Publication date: 23 December 2013

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

Full work available at URL: https://doi.org/10.1080/00207160.2012.757073

zbMATH Keywords

image processingminimizationdenoisingreconstructionsegmentationmultiplicative noisesurface fairingdeblurring

Mathematics Subject Classification ID

Multigrid methods; domain decomposition for boundary value problems involving PDEs (65N55) Numerical optimization and variational techniques (65K10) Computing methodologies for image processing (68U10) Energy minimization in equilibrium problems in solid mechanics (74G65) Inverse problems in equilibrium solid mechanics (74G75) Image processing (compression, reconstruction, etc.) in information and communication theory (94A08)

Related Items (12)

Two new preconditioners for mean curvature-based image deblurring problem ⋮ Estimation of time-dependent Hurst exponents with variational smoothing and application to forecasting foreign exchange rates ⋮ An effective algorithm for mean curvature-based image deblurring problem ⋮ A two-level method for image denoising and image deblurring models using mean curvature regularization ⋮ Multiplicative noise removal combining a total variation regularizer and a nonconvex regularizer ⋮ Improving image deblurring ⋮ Analysis of the CCFD method for MC-based image denoising problems ⋮ PDE-based hyperbolic-parabolic model for image denoising with forward-backward diffusivity ⋮ An additive convolution model for fast restoration of nonuniform blurred images ⋮ A strongly convergent Krasnosel'skiǐ-Mann-type algorithm for finding a common fixed point of a countably infinite family of nonexpansive operators in Hilbert spaces ⋮ Fractional diffusion equation-based image denoising model using CN–GL scheme ⋮ An iterative decoupled method with weighted nuclear norm minimization for image restoration

Uses Software

• FAIR.m

Cites Work

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• Noise Removal Using Smoothed Normals and Surface Fitting
• FAIR
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• Matrix Preconditioning Techniques and Applications
• Computational Methods for Inverse Problems
• Image Processing and Analysis
• Multigrid Algorithm for High Order Denoising

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