A parametric model, and a corresponding parameter estimation algorithm for unwrapping two-dimensional phase functions, are presented. While conventional approaches to the 2-D phase unwrapping problem usually involve local analysis of the phase image, the proposed algorithm performs global analysis of the observed signal and hence it is insensitive to local errors. In its first step the algorithm fits a 2-D polynomial model to the observed phase. The estimated phase is then used as a reference information which directs the actual phase unwrapping process: The phase of each sample of the observed field is unwrapped by increasing (decreasing) it by the multiple of 2π which is the nearest to the estimated phase value at this coordinate. In practical 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 fitted with its own model. Once the phase model of the observed field has been estimated we can repeat the model-based unwrapping procedure described earlier for the case of a single segment and a single model field.