MODEL-BASED PHASE UNWRAPPING OF 2-D SIGNALS

A parametric model and a corresponding parameter estimation algorithm for unwrapping 2-D phase functions are presented. The proposed algorit hm performs global analysis of the observed signal. Since this analysi s is based on parametric model fitting, the proposed phase unwrapping algorithm has low sensitivity to phase aliasing due to low sampling ra tes and noise, as well as to local errors, In its first step, the algo rithm fits a 2-D polynomial model to the observed phase. The estimated phase is then used as a reference information that directs the actual phase unwrapping process: The phase of each sample of the observed fi eld is unwrapped by increasing (decreasing) it by the multiple of 2 pi , which is the nearest to the difference between the principle value o f the phase and the estimated phase value at this coordinate, In pract ical applications, the entire phase function cannot be approximated by a single 2-D polynomial model, Hence, the observed field is segmented , and each segment is fit with its own model, Once the phase model of the observed field has been estimated, we can repeat the model-based u ncapping procedure described earlier for the case of a single segment and a single model field.