Title :
Reconstruction algorithms for electromagnetic imaging
Author :
Pastorino, M. ; Caorsi, S. ; Massa, A. ; Randazzo, A.
Author_Institution :
Dept. of Biophys. & Electron. Eng., Genoa Univ., Italy
fDate :
6/24/1905 12:00:00 AM
Abstract :
Two algorithms for image reconstruction in electromagnetic imaging are proposed. The first approach concerns the application of a hybrid version of the genetic algorithm to tomographic imaging of dielectric configurations. In the second approach, buried inhomogeneities are schematized as multilayer infinite dielectric cylinders with elliptic cross sections. An efficient recursive analytical procedure is used for the forward scattering computation. A cost function is constructed in which the field is expressed in a series solution of Mathieu functions. Starting with the input scattered data, the iterative minimization of the function is performed by a new optimization method called a memetic algorithm.
Keywords :
electromagnetic wave scattering; genetic algorithms; image reconstruction; inverse problems; iterative methods; minimisation; recursive estimation; tomography; EM imaging reconstruction algorithms; Mathieu functions series solution; buried inhomogeneities; cost functions; dielectric configuration tomographic imaging; electromagnetic imaging systems; elliptic cross section dielectric cylinders; forward scattering computation; hybrid genetic algorithms; input scattered data; inversion techniques; iterative minimization; memetic algorithms; multilayer infinite dielectric cylinders; recursive analytical procedures; Cost function; Dielectrics; Electromagnetic scattering; Genetic algorithms; Image reconstruction; Iterative methods; Minimization methods; Nonhomogeneous media; Reconstruction algorithms; Tomography;
Conference_Titel :
Instrumentation and Measurement Technology Conference, 2002. IMTC/2002. Proceedings of the 19th IEEE
Print_ISBN :
0-7803-7218-2
DOI :
10.1109/IMTC.2002.1007215