Constrained Restoration and the Recovery of Discontinuities
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
Oscillating Patterns in Image Processing and Nonlinear Evolution Equations: The Fifteenth Dean Jacqueline B. Lewis Memorial Lectures
Analysis of Half-Quadratic Minimization Methods for Signal and Image Recovery
SIAM Journal on Scientific Computing
Image Restoration with Discrete Constrained Total Variation Part I: Fast and Exact Optimization
Journal of Mathematical Imaging and Vision
Mathematical Problems in Image Processing: Partial Differential Equations and the Calculus of Variations (Applied Mathematical Sciences)
On Total Variation Minimization and Surface Evolution Using Parametric Maximum Flows
International Journal of Computer Vision
A note on the bregmanized total variation and dual forms
ICIP'09 Proceedings of the 16th IEEE international conference on Image processing
Deterministic edge-preserving regularization in computed imaging
IEEE Transactions on Image Processing
Forward-and-backward diffusion processes for adaptive image enhancement and denoising
IEEE Transactions on Image Processing
The Equivalence of Half-Quadratic Minimization and the Gradient Linearization Iteration
IEEE Transactions on Image Processing
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This paper describes an approach for performing image restoration using a coupled differential system that both simplifies the image while preserving its contrast. The first process corresponds to a differential inclusion involving discrete Total Variations that simplifies more and more the observed image as time evolves. The second one extracts some pertinent geometric information contained in the series of simplified images and recovers the constrast using Bregman distances. Convergence and exact computational properties of the method rely on the discrete and combinatorial properties of discrete Total Variations.