Detecting and imaging dielectric objects from real data: A shape-based approach
In this paper we investigate the performance of a shape-reconstruction technique as tested on the 'Marseille data'. This approach, which is based on a level set technique, offers several advantages compared to other approaches, as for example well-defined boundaries and the incorporation of an intrinsic regularization in the form of a priori assumptions regarding the general structures in the medium. The level set strategy (which is an implicit representation of the shapes) frees us from topological restrictions during this reconstruction process. Our algorithm is aiming at, not only detecting the objects, but simultaneously determining their approximate locations, sizes and dielectric properties. The numerical experiments show the utility of this method. (C) 2009 Elsevier Ltd. All rights reserved.
real data level sets microwave imaging