Phase Cost Indicator-Guided Central Difference Information Filter 2-D Phase Unwrapping Approach

Model based phase unwrapping of 2-D signals

A parametric model and a corresponding parameter estimation algorithm for unwrapping two-dimensional phase functions, are presented. The proposed algorithm performs global analysis of the observed signal. Since this analysis is based on parametric model tting, the proposed phase unwrapping algorithm has low sensitivity to phase aliasing due to low sampling rates and noise, as well as to local e...

2-D phase unwrapping and instantaneous frequency estimation

Half-quadratic cost functions for phase unwrapping.

We present a generic regularized formulation, based on robust half-quadratic regularization, for unwrapping noisy and discontinuous wrapped phase maps. Two cases are presented: the convex case and the nonconvex case. The unwrapped phase with the convex formulation is unique and robust to noise; however, the convex function solution deteriorates as a result of real discontinuities in phase maps....

Phase Unwrapping

Phase unwrapping is the reconstruction of the originaltrue phase of a wave from its modulo 2p values. It origi-nates in a variety of applications, such as synthetic aper-ture radar, magnetic resonance imaging, and adaptiveoptics. In this article, the problem of two-dimensionalphase unwrapping is defined and the challenges are ad-dressed. A variety of established approach...

InSAR Phase Unwrapping: A Bayesian Approach

The paper proposes a Bayesian approach to absolute phase (not simply modulo-2π) estimation in interferometric aperture radar (InSAR). The observation density is 2π-periodic and accounts for the interferometric pair decorrelation and the system noise; the a priori probability of the absolute phase is modeled by a compound Gauss Markov random field (CGMRF). To compute the absolute phase estimate ...