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Variational Methods

In Imaging and Geometric Control

Edited by: Maïtine Bergounioux, Gabriel Peyré, Christoph Schnörr, Jean-Baptiste Caillau and Thomas Haberkorn

With a focus on the interplay between mathematics and applications of imaging, the first part covers topics from optimization, inverse problems and shape spaces to computer vision and computational anatomy. The second part is geared towards geometric control and related topics, including Riemannian geometry, celestial mechanics and quantum control.

Part I
Second-order decomposition model for image processing: numerical experimentation
Optimizing spatial and tonal data for PDE-based inpainting
Image registration using phase・amplitude separation
Rotation invariance in exemplar-based image inpainting
Convective regularization for optical flow
A variational method for quantitative photoacoustic tomography with piecewise constant coefficients
On optical flow models for variational motion estimation
Bilevel approaches for learning of variational imaging models
Part II
Non-degenerate forms of the generalized Euler・Lagrange condition for state-constrained optimal control problems
The Purcell three-link swimmer: some geometric and numerical aspects related to periodic optimal controls
Controllability of Keplerian motion with low-thrust control systems
Higher variational equation techniques for the integrability of homogeneous potentials
Introduction to KAM theory with a view to celestial mechanics
Invariants of contact sub-pseudo-Riemannian structures and Einstein・Weyl geometry
Time-optimal control for a perturbed Brockett integrator
Twist maps and Arnold diffusion for diffeomorphisms
A Hamiltonian approach to sufficiency in optimal control with minimal regularity conditions: Part I

Author Information

Maïtine Bergounioux, Université d'Orléans, France.

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Audience: Researchers in Mathematics (especially optimization), Engineering, Computer Science and Imaging.