A note on the bregmanized total variation and dual forms

Authors:
Jérôme Darbon;Igor Ciril;Antonio Marquina;Tony F. Chan;Stanley Osher
Affiliations:
UCLA, Mathematics Department, Los Angeles;LMCI Laboratory, IPSA, Paris , France and Departement of embeded systems, ESIEE, Paris, France;Departamento de Matematica Aplicada, Universidad de Valencia, Spain;UCLA, Mathematics Department, Los Angeles;UCLA, Mathematics Department, Los Angeles
Venue:
ICIP'09 Proceedings of the 16th IEEE international conference on Image processing
Year:
2009

Citing 4
Cited 1

Constrained Restoration and the Recovery of Discontinuities

IEEE Transactions on Pattern Analysis and Machine Intelligence
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
The Equivalence of Half-Quadratic Minimization and the Gradient Linearization Iteration

IEEE Transactions on Image Processing

Image denoising with a constrained discrete total variation scale space

DGCI'11 Proceedings of the 16th IAPR international conference on Discrete geometry for computer imagery

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Abstract

This paper considers two approaches to perform image restoration while preserving the contrast. The first one is the Total Variation-based Bregman iterations while the second consists in the minimization of an energy that involves robust edge preserving regularization. We show that these two approaches can be derived form a common framework. This allows us to deduce new properties and to extend and generalize these two previous approaches.