PDE-constrained optimization problems have a wide range of applications across mathematics and applied science, so it is important to develop feasible and robust methods to solve such problems. In this talk we focus on an inverse problem model for image metamorphosis, where the PDE constraint is given by a transport equation. We derive fast iterative methods for the solution of the resulting matrix systems, using effective saddle-point preconditioners.

This presentation is part of Minisymposium “MS62 - Imaging models with non-linear constraints (2 parts)”
organized by: Tuomo Valkonen (University of Liverpool) , Juan Carlos De Los Reyes (Escuela Politécnica Nacional) .

Authors:

John Pearson (University of Edinburgh)

Keywords:

image representation, inverse problems, nonlinear optimization, numerical linear algebra, partial differential equation models