Nov 18 – 22, 2013
MPI Munich
Europe/Berlin timezone

Basics 4: Information field theory - from data to images (lecture)

Nov 19, 2013, 9:00 AM
1h 30m
MPI Munich

MPI Munich

Foehringer Ring 6 D-80805 Munich


Dr Torsten Ensslin (MPA)


The problem of reconstrucing an image or a function from data is generally ill-posed. The desired signal has an infinite number of degrees of freedom whereas the data is only providing a finite number of constraints. Additional statistical information and other knowledge has to be used to regularize the problem. Information field theory permits us to formulate signal inference problems rigorously using probabilistic language to combine data and knowledge. It helps us to exploit existing methods developed for field theories to derive optimal reconstruction algorithms. In this course, an introduction to the basic principles of information field theory will be given and illustrate by concrete examples from astrophysical applications.

Presentation materials