CARMA Seminar

4:00 pm

Friday, 22nd Nov 2019

SR202, SR Building

Prof Ke Chen

(University of Liverpool)

Optimization Methods for Inverse Problems from Imaging

Optimization is often viewed as an active and yet mature research field. However the recent and rapid development in the emerging field of Imaging Sciences has provided a very rich source of new problems as well as big challenges for optimization. Such problems having typically non-smooth and non-convex functionals demand urgent and major improvements on traditional solution methods suitable for convex and differentiable functionals.

This talk presents a limited review of a set of Imaging Models which are investigated by the Liverpool group as well as other groups, out of the huge literature of related works. We start with image restoration models regularised by the total variation and high order regularizers. We then show some results from image registration to align a pair of images which may be in single-modality or multimodality with the latter very much non-trivial. Next we review the variational models for image segmentation. Finally we show some recent attempts to extend our image registration models from more traditional optimization to the Deep Learning framework.

Joint work with recent and current collaborators including D P Zhang, A Theljani, M Roberts, J P Zhang, A Jumaat, T Thompson.