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.