Innovative CS imaging methods in transformed domains

Abstract

The solution of linear microwave imaging problems is considered in this work through innovative classes of Compressive Sensing (CS) methods. More in detail, the formulation of the inversion process in transformed domains with sparseness-regularized formulations is considered. Representative numerical examples illustrating the potentialities and limitations of the arising CS inversion approaches are reported.