Improving a shape reconstruction algorithm with thresholds and multi-view data

This paper deals with the reconstruction of the shape of unknown perfectly conducting objects from the knowledge of the scattered electric far field in a two-dimensional geometry. By adopting the Kirchhoff approximation, the problem is cast as a linear inverse one and is solved by resorting to the Singular Value Decomposition (SVD) approach. The finiteness of the available data along with the presence of the noise make undesired features on the reconstructed image arise. We here give some criteria for the choice of a threshold to cut them out from the reconstructions. Furthermore, we illustrate the processing of multi-view data.