In this talk we consider simultaneous blind deconvolution of r signals from their noisy superposition, a problem also referred to as blind demixing and deconvolution. We will show that recovery of the unknown functions is possible using convex programming, if the number of measurements is close to the degrees of freedom.

This presentation is part of Minisymposium “MS25 - Bilinear and quadratric problems in imaging”
organized by: Felix Krahmer (Technical University of Munich, Department of Mathematics) , Kristian Bredies (Universität Graz) .

Authors:

Dominik Stoeger (Technical University of Munich)

Peter Jung (Technical University of Berlin)

Felix Krahmer (Technical University of Munich, Department of Mathematics)

Keywords:

image deblurring, image reconstruction, inverse problems, nonlinear optimization, stochastic processes