|
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.
News
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!
|
|