581 research outputs found
A function space framework for structural total variation regularization with applications in inverse problems
In this work, we introduce a function space setting for a wide class of
structural/weighted total variation (TV) regularization methods motivated by
their applications in inverse problems. In particular, we consider a
regularizer that is the appropriate lower semi-continuous envelope (relaxation)
of a suitable total variation type functional initially defined for
sufficiently smooth functions. We study examples where this relaxation can be
expressed explicitly, and we also provide refinements for weighted total
variation for a wide range of weights. Since an integral characterization of
the relaxation in function space is, in general, not always available, we show
that, for a rather general linear inverse problems setting, instead of the
classical Tikhonov regularization problem, one can equivalently solve a
saddle-point problem where no a priori knowledge of an explicit formulation of
the structural TV functional is needed. In particular, motivated by concrete
applications, we deduce corresponding results for linear inverse problems with
norm and Poisson log-likelihood data discrepancy terms. Finally, we provide
proof-of-concept numerical examples where we solve the saddle-point problem for
weighted TV denoising as well as for MR guided PET image reconstruction
A class of second-order geometric quasilinear hyperbolic PDEs and their application in imaging science
In this paper, we study damped second-order dynamics, which are quasilinear
hyperbolic partial differential equations (PDEs). This is inspired by the
recent development of second-order damping systems for accelerating energy
decay of gradient flows. We concentrate on two equations: one is a damped
second-order total variation flow, which is primarily motivated by the
application of image denoising; the other is a damped second-order mean
curvature flow for level sets of scalar functions, which is related to a
non-convex variational model capable of correcting displacement errors in image
data (e.g. dejittering). For the former equation, we prove the existence and
uniqueness of the solution. For the latter, we draw a connection between the
equation and some second-order geometric PDEs evolving the hypersurfaces which
are described by level sets of scalar functions, and show the existence and
uniqueness of the solution for a regularized version of the equation. The
latter is used in our algorithmic development. A general algorithm for
numerical discretization of the two nonlinear PDEs is proposed and analyzed.
Its efficiency is demonstrated by various numerical examples, where simulations
on the behavior of solutions of the new equations and comparisons with
first-order flows are also documented
Existence, iteration procedures and directional differentiability for parabolic QVIs
We study parabolic quasi-variational inequalities (QVIs) of obstacle type.
Under appropriate assumptions on the obstacle mapping, we prove the existence
of solutions of such QVIs by two methods: one by time discretisation through
elliptic QVIs and the second by iteration through parabolic variational
inequalities (VIs). Using these results, we show the directional
differentiability (in a certain sense) of the solution map which takes the
source term of a parabolic QVI into the set of solutions, and we relate this
result to the contingent derivative of the aforementioned map. We finish with
an example where the obstacle mapping is given by the inverse of a parabolic
differential operator.Comment: 41 page
Stability of the solution set of quasi-variational inequalities and optimal control
For a class of quasi-variational inequalities (QVIs) of obstacle-type the
stability of its solution set and associated optimal control problems are
considered. These optimal control problems are non-standard in the sense that
they involve an objective with set-valued arguments. The approach to study the
solution stability is based on perturbations of minimal and maximal elements of
the solution set of the QVI with respect to {monotone} perturbations of the
forcing term. It is shown that different assumptions are required for studying
decreasing and increasing perturbations and that the optimization problem of
interest is well-posed.Comment: 29 page
Optimal bilinear control of Gross-Pitaevskii equations
A mathematical framework for optimal bilinear control of nonlinear
Schr\"odinger equations of Gross-Pitaevskii type arising in the description of
Bose-Einstein condensates is presented. The obtained results generalize earlier
efforts found in the literature in several aspects. In particular, the cost
induced by the physical work load over the control process is taken into
account rather then often used - or -norms for the cost of the
control action. Well-posedness of the problem and existence of an optimal
control is proven. In addition, the first order optimality system is rigorously
derived. Also a numerical solution method is proposed, which is based on a
Newton type iteration, and used to solve several coherent quantum control
problems.Comment: 30 pages, 14 figure
Optimal boundary control of the isothermal semilinear Euler equation for gas dynamics on a network
The analysis and boundary optimal control of the nonlinear transport of gas on a network of pipelines is considered. The evolution of the gas distribution on a given pipe is modeled by an isothermal semilinear compressible Euler system in one space dimension. On the network, solutions satisfying (at nodes) the Kirchhoff flux continuity conditions are shown to exist in a neighborhood of an equilibrium state. The associated nonlinear optimization problem then aims at steering such dynamics to a given target distribution by means of suitable (network) boundary controls while keeping the distribution within given (state) constraints. The existence of local optimal controls is established and a corresponding Karush--Kuhn--Tucker (KKT) stationarity system with an almost surely non--singular Lagrange multiplier is derived
Generating structured non-smooth priors and associated primal-dual methods
The purpose of the present chapter is to bind together and extend some recent developments regarding data-driven non-smooth regularization techniques in image processing through the means of a bilevel minimization scheme. The scheme, considered in function space, takes advantage of a dualization framework and it is designed to produce spatially varying regularization parameters adapted to the data for well-known regularizers, e.g. Total Variation and Total Generalized variation, leading to automated (monolithic), image reconstruction workflows. An inclusion of the theory of bilevel optimization and the theoretical background of the dualization framework, as well as a brief review of the aforementioned regularizers and their parameterization, makes this chapter a self-contained one. Aspects of the numerical implementation of the scheme are discussed and numerical examples are provided
On the density of classes of closed convex sets with pointwise constraints in Sobolev spaces
For a Banach space X of R^M-valued functions on a Lipschitz domain, let K(X) ⊂ X be a closed convex set arising from pointwise constraints on the value of the function, its gradient or its divergence, respectively. The main result of the paper establishes, under certain conditions, the density of K(X_0) in K(X_1) where X_0 is densely and continuously embedded in X_1. The proof is constructive, utilizes the theory of mollifiers and can be applied to Sobolev spaces such as H (div,Ω) and W1,p(Ω), in particular. It is also shown that such a density result cannot be expected in general.Peer Reviewe
Optimal control of geometric partial differential equations
Optimal control problems for geometric (evolutionary) partial differential inclusions are considered. The focus is on problems which, in addition to the nonlinearity due to geometric evolution, contain optimization theoretic challenges because of non-smoothness. The latter might stem from energies containing non-smooth constituents such as obstacle-type potentials or terms modeling, e.g., pinning phenomena in microfluidics. Several techniques to remedy the resulting constraint degeneracy when deriving stationarity conditions are presented. A particular focus is on Yosida-type mollifications approximating the original degenerate problem by a sequence of nondegenerate nonconvex optimal control problems. This technique is also the starting point for the development of numerical solution schemes. In this context, also dual-weighted residual based error estimates are addressed to facilitate an adaptive mesh refinement. Concerning the underlying state model, sharp and diffuse interface formulations are discussed. While the former always allows for accurately tracing interfacial motion, the latter model may be dictated by the underlying physical phenomenon, where near the interface mixed phases may exist, but it may also be used as an approximate model for (sharp) interface motion. In view of the latter, (sharp interface) limits of diffuse interface models are addressed. For the sake of presentation, this exposition confines itself to phase field type diffuse interface models and, moreover, develops the optimal control of either of the two interface models along model applications. More precisely, electro-wetting on dielectric is used in the sharp interface context, and the control of multiphase fluids involving spinodal decomposition highlights the phase field technique. Mathematically, the former leads to a Hele-Shaw flow with geometric boundary conditions involving a complementarity system due to contact line pinning, and the latter gives rise to a Cahn-Hilliard Navier-Stokes model including a non-smooth obstacle type potential leading to a variational inequality constraint
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