An introduction to continuous optimization for imaging
A Chambolle, T Pock - Acta Numerica, 2016 - cambridge.org
A large number of imaging problems reduce to the optimization of a cost function, with
typical structural properties. The aim of this paper is to describe the state of the art in …
typical structural properties. The aim of this paper is to describe the state of the art in …
Higher-order total variation approaches and generalisations
Over the last decades, the total variation (TV) has evolved to be one of the most broadly-
used regularisation functionals for inverse problems, in particular for imaging applications …
used regularisation functionals for inverse problems, in particular for imaging applications …
An introduction to total variation for image analysis
A Chambolle, V Caselles, D Cremers… - … numerical methods for …, 2010 - degruyter.com
These notes address various theoretical and practical topics related to Total Variationbased
image reconstruction. They focus first on some theoretical results on functions which …
image reconstruction. They focus first on some theoretical results on functions which …
[图书][B] Image processing and analysis: variational, PDE, wavelet, and stochastic methods
No time in human history has ever witnessed such explosive influence and impact of image
processing on modern society, sciences, and technologies. From nanotechnologies …
processing on modern society, sciences, and technologies. From nanotechnologies …
An algorithm for minimizing the Mumford-Shah functional
In this work we revisit the Mumford-Shah functional, one of the most studied variational
approaches to image segmentation. The contribution of this paper is to propose an algorithm …
approaches to image segmentation. The contribution of this paper is to propose an algorithm …
Total variation minimization and a class of binary MRF models
A Chambolle - … Workshop on Energy Minimization Methods in …, 2005 - Springer
We observe that there is a strong connection between a whole class of simple binary MRF
energies and the Rudin-Osher-Fatemi (ROF) Total Variation minimization approach to …
energies and the Rudin-Osher-Fatemi (ROF) Total Variation minimization approach to …
A convex relaxation approach for computing minimal partitions
In this work we propose a convex relaxation approach for computing minimal partitions. Our
approach is based on rewriting the minimal partition problem (also known as Potts model) in …
approach is based on rewriting the minimal partition problem (also known as Potts model) in …
A convex approach to minimal partitions
We describe a convex relaxation for a family of problems of minimal perimeter partitions. The
minimization of the relaxed problem can be tackled numerically: we describe an algorithm …
minimization of the relaxed problem can be tackled numerically: we describe an algorithm …
Global solutions of variational models with convex regularization
We propose an algorithmic framework for computing global solutions of variational models
with convex regularity terms that permit quite arbitrary data terms. While the minimization of …
with convex regularity terms that permit quite arbitrary data terms. While the minimization of …
Recovering piecewise smooth multichannel images by minimization of convex functionals with total generalized variation penalty
K Bredies - Efficient Algorithms for Global Optimization Methods in …, 2014 - Springer
We study and extend the recently introduced total generalized variation (TGV) functional for
multichannel images. This functional has already been established to constitute a well …
multichannel images. This functional has already been established to constitute a well …