Title: Inpainting and Visual Interpolation

 Abstract: Inpainting, or image interpolation, has broad applications
  in visual perception, digital media, and information
  technologies. Compared with other classical interpolation problems
  (such as polynomial-, spline-, Shannon- or wavelet-interpolations),
  inpainting imposes extra challenges mainly due to the complexity of
  both missing domains and missing signals, especially the geometric
  features of images. In this talk, we focus on our recent efforts in
  applying the variational-PDE approach to inpainting, and reveal some
  major applications of nonlinear PDEs, stochastic modeling, geometric
  measure theory, and Gamma-convergence in contemporary mathematical
  imaging and vision.  (Joint work with several authors in the past
  few years, especially with the applied math group at UCLA.)