Multidimensional Orientation Estimation with Applications to Texture Analysis and Optical Flow
IEEE Transactions on Pattern Analysis and Machine Intelligence
Nonlinear total variation based noise removal algorithms
Proceedings of the eleventh annual international conference of the Center for Nonlinear Studies on Experimental mathematics : computational issues in nonlinear science: computational issues in nonlinear science
A Nonlinear Primal-Dual Method for Total Variation-Based Image Restoration
SIAM Journal on Scientific Computing
Handbook of Image and Video Processing
Handbook of Image and Video Processing
High-Order Total Variation-Based Image Restoration
SIAM Journal on Scientific Computing
SIAM Journal on Numerical Analysis
The Primal-Dual Active Set Strategy as a Semismooth Newton Method
SIAM Journal on Optimization
An Algorithm for Total Variation Minimization and Applications
Journal of Mathematical Imaging and Vision
A Variational Approach to Remove Outliers and Impulse Noise
Journal of Mathematical Imaging and Vision
Efficient Minimization Methods of Mixed l2-l1 and l1-l1 Norms for Image Restoration
SIAM Journal on Scientific Computing
Augmented Lagrangian Method, Dual Methods and Split Bregman Iteration for ROF Model
SSVM '09 Proceedings of the Second International Conference on Scale Space and Variational Methods in Computer Vision
An Efficient TVL1 Algorithm for Deblurring Multichannel Images Corrupted by Impulsive Noise
SIAM Journal on Scientific Computing
The Split Bregman Method for L1-Regularized Problems
SIAM Journal on Imaging Sciences
A New Alternating Minimization Algorithm for Total Variation Image Reconstruction
SIAM Journal on Imaging Sciences
An Efficient Primal-Dual Method for $L^1$TV Image Restoration
SIAM Journal on Imaging Sciences
Automatic parameter selection for denoising algorithms using a no-reference measure of image content
IEEE Transactions on Image Processing
SIAM Journal on Imaging Sciences
Anisotropic diffusion of multivalued images with applications to color filtering
IEEE Transactions on Image Processing
Color TV: total variation methods for restoration of vector-valued images
IEEE Transactions on Image Processing
Fourth-order partial differential equations for noise removal
IEEE Transactions on Image Processing
Noise adaptive soft-switching median filter
IEEE Transactions on Image Processing
Selective removal of impulse noise based on homogeneity level information
IEEE Transactions on Image Processing
IEEE Transactions on Image Processing
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Total variation (TV) model is a classical image restoration model. The introduction of this model is revolutionary, since TV can preserve discontinuities (edges) while removing other unwanted fine scale details. Lots of efficient methods have been successfully devised and applied to image restoration. However, many of them are sensitive to numerical errors. In this paper, we will first introduce a robust TV based model, which regularizes the restoration using joint isotropic and anisotropic total variation to suppress numerical errors, then present an efficiently iterative algorithm using augmented Lagrangian method. By separating the problem into three sub-problems, the algorithm can be solved efficiently either via fast Fourier transform (FFT) or closed form solution in each iteration. Finally, we use metric Q which is based upon singular value decomposition of local image gradient matrix to effectively measure true image content. Extensive numerical experiments demonstrate that our proposed model has better performance than several state-of-the-art algorithms in terms of signal-noise ratio and recovered image quality.