MICROWAVE IMAGING BASED ON A MARKOV RANDOM-FIELD MODEL

A new approach to microwave imaging of 2-D inhomogeneous dielectric scatterers is presented. The method is developed in the space domain, and Markov Random Fields are used to obtain a model of the distributions of dielectric features in the scattering region. In this way, a-priori knowledge can be easily inserted in the imaging scheme. This stochastic approach gives rise to a functional equation that can be minimized by using a simulated annealing algorithm. An iterative scheme is derived that allows one to bypass the need for storing large matrices in the computer. Numerical simulation results, confirming the capabilities and effectiveness of the proposed method, are reported. Solutions have generally been obtained in few steps, and seem better than those obtained by other imaging techniques in the space domain. The capability of the algorithm to operate in a strongly noisy environment is also proved.