An improved least-squares method for INSAR phase unwrapping

An improved least-squares phase unwrapping method is proposed by adding a constraint term which gives a smooth unwrapped phase in regions where the measured phase is corrupt. Moreover, the wavelet noise-removal technique is used for both real and imaginary parts of INSAR data. The phase partial derivatives obtained from filtered INSAR data are applied to calculate the unwrapped phase to relieve the slope underestimation problem. The derived equations for least-squares unwrapped phase are solved using Newton iteration under Gauss-Seidel relaxation schemes. A multigrid algorithm is used to speed up the convergence of the iteration. Results on simulated and real ERS-1/2 data demonstrate the efficiency and precision of this improved least-squares method