Fachvortrag in englischer Sprache

Compressed sensing and sparse recovery of signals and images has become a popular topic recently. In this talk we provide a dual viewpoint on sparse recovery and discuss (adaptive) inverse scale space methods for the efficient computational solutions. Surprisingly the latter connect various different computational approaches for sparse recovery such as variational, iterative, and greedy methods, and they can be generalized from l 1-minimization to a wider range of variational problems. This is also relevant for some applications we discuss, ranging from image re­construction to the unmixing of spectral data. 

Speaker: Prof. Dr. Martin Burger, University Münster