Variational Methods

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