The ZπM Algorithm for Interferometric Image Reconstruction in SAR/SAS

The paper presents an effective algorithm for absolute phase (not simply modulo-2π) estimation from incomplete, noisy, and modulo-2π observations in interferometric aperture radar and sonar (InSAR/InSAS). The adopted framework is also representative of other applications such as optical interferometry, magnetic resonance imaging, and diffraction tomography. The Bayesian viewpoint is adopted; the observation density is 2π-periodic and accounts for the interferometric pair decorrelation and system noise; the a priori probability of the absolute phase is modelled by a Compound Gauss Markov random field (CGMRF) tailored to piecewise smooth absolute phase images. We propose an iterative scheme for the computation of the maximum a posteriori probability (MAP) phase estimate. Each iteration embodies a discrete optimization step (Z-step), implemented by network programming techniques, and an iterative conditional modes (ICM) step (π-step). Accordingly, the algorithm is termed ZπM, where the letter M stands for maximization. A set of experimental results, comparing the proposed algorithm with alternative approaches, illustrates the effectiveness of the proposed method. EDICS: 3-OTHC (Other Image Formation) or 3-RADR (Radar Imaging ) Permission to publish this abstract separately is granted. This work was supported by the Fundação para a Ciência e Tecnologia, under the project POSI/34071/CPS/2000. J. Dias is with the Instituto Superior Técnico, Instituto de Telecomunicações, Torre Norte, Piso 10, Av. Rovisco Pais,1049-001 Lisboa, Portugal, Phone: 351 21 8418466, Fax: 351 21 8418472, Email: [email protected] J. Leitão is with the Instituto Superior Técnico, Instituto de Telecomunicações, Torre Norte, Piso 10, Av. Rovisco Pais,1049-001 Lisboa, Portugal, Email: [email protected] IEEE TRANSACTIONS ON IMAGE PROCESSING, VOL. XX, NO. Y, MONTH 2001 2