INDAM intensive period

Computational Methods for Inverse Problems in Imaging

Como, May 21 – July 20, 2018

Welcome to the home page of the INDAM intensive period on "Computational Methods for Inverse Problems in Imaging".

An appropriate formulation of ill-posed image restoration problems requires an accurate mathematical modeling, which normally leads to the delicate issue of applying regularization techniques. As a result, the solution of inverse problems is in general reduced to a constrained minimization of suitable functionals with special structure. The computational methods to efficiently face these problems are based on a combination of new numerical linear algebra and optimization algorithms. For the case where the given application requires to recover special features of the images, numerical schemes relying on variational methods and/or on the notion of sparsity have been designed. By taking advantage of multilevel techniques based on wavelet or shearlet decomposition, robust algorithms for image reconstruction can be devised, starting from incomplete and/or truncated data. Several current and challenging applications appear in astronomy (such as, for example, blind deconvolution of interferometric images of the Large Binocular Telescope Interferometer), microscopy (e.g., reconstruction of multiple images in STED microscopy or images acquired by means of Differential Interference Contrast microscopy), biomedical imaging (e.g., reconstruction of a small region of interest from truncated computed tomography (CT) projection data, reconstruction of images from microwave systems, reconstruction methods in PET and MRI imaging in functional medicine).

The intensive period starts with an introductory summer school, while an advanced workshop completes the activities. The thematic weeks in the middle of the period are devoted to special applications or classes of numerical methods.


May, 2018
The site has been updated with info on Calendar, Venues and Participants.

December, 2017
You can now register from this page .

November, 2017
Website is up!