Recently, several different approaches for digital inpainting have been proposed in the literature. We give a review and introduce
a novel approach based on the complex Ginzburg-Landau equation. The use of this equation is motivated by some of its remarkable
analytical properties. While common inpainting technology is especially designed for restorations of two dimensional image
data, the Ginzburg-Landau equation can straight forwardly be applied to restore higher dimensional data, which has applications
in frame interpolation, improving sparsely sampled volumetric data and to fill in fragmentary surfaces. The latter application
is of importance in architectural heritage preservation. We discuss a stable and efficient scheme for the numerical solution
of the Ginzburg-Landau equation and present some numerical experiments. We compare the performance of our algorithm with other
well established methods for inpainting.
Keywords Ginzburg-Landau equation - inpainting - diffusion filtering - non-linear partial differential equations - variational problems