Interferometric image reconstruction as a nonlinear Bayesian estimation problem

Author

Leitão, Josè M N ; Figueiredo, Mário A T

Author_Institution

Dept. de Engenharia Electrotecnica e de Comput., Inst. Superior Tecnico, Lisbon, Portugal

Volume

2

fYear

1995

fDate

23-26 Oct 1995

Firstpage

453

Abstract

This paper formulates interferometric image reconstruction as a 2D absolute phase estimation problem. The original phase image is modeled as a sample of a Gauss Markov random field; the observations are the noisy in-phase (cosine) and quadrature (sine) images. The proposed solution combines features of the iterated conditional modes algorithm with nonlinear stochastic absolute phase estimation concepts. Examples of important applications are: interferometric synthetic aperture radar, optical interferometry, magnetic resonance imaging, and diffraction tomography

Keywords

Bayes methods; Gaussian processes; Markov processes; biomedical NMR; image reconstruction; iterative methods; light interferometry; phase estimation; random processes; synthetic aperture radar; tomography; 2D absolute phase estimation problem; Gauss Markov random field; cosine images; diffraction tomography; interferometric image reconstruction; interferometric synthetic aperture radar; iterated conditional modes algorithm; magnetic resonance imaging; noisy in-phase sine images; nonlinear Bayesian estimation problem; nonlinear stochastic absolute phase estimation; optical interferometry; phase image; quadrature images; sine images; Bayesian methods; Gaussian processes; Image reconstruction; Magnetic noise; Markov random fields; Optical noise; Phase estimation; Phase noise; Stochastic processes; Synthetic aperture radar interferometry;

fLanguage

English

Publisher

ieee

Conference_Titel

Image Processing, 1995. Proceedings., International Conference on

Conference_Location

Washington, DC

Print_ISBN

0-8186-7310-9

Type

conf

DOI

10.1109/ICIP.1995.537513

Filename

537513