Abstract

A novel hybrid genetic algorithm (HGA) is proposed to solve the branch-cut phase unwrapping problem. It employs both local and global search methods. The local search is implemented by using the nearest-neighbor method, whereas the global search is performed by using the genetic algorithm. The branch-cut phase unwrapping problem [a nondeterministic polynomial (NP-hard) problem] is implemented in a similar way to the traveling-salesman problem, a very-well-known combinational optimization problem with profound research and applications. The performance of the proposed algorithm was tested on both simulated and real wrapped phase maps. The HGA is found to be robust and fast compared with three well-known branch-cut phase unwrapping algorithms.

© 2007 Optical Society of America

Residue vector, an approach to branch-cut placement in phase unwrapping: theoretical study

Salah A. Karout, Munther A. Gdeisat, David R. Burton, and Michael J. Lalor
Appl. Opt. 46(21) 4712-4727 (2007)

Unwrapping noisy phase maps by use of a minimum-cost-matching algorithm

J. R. Buckland, J. M. Huntley, and S. R. E. Turner
Appl. Opt. 34(23) 5100-5108 (1995)

Fast and robust three-dimensional best path phase unwrapping algorithm

Hussein S. Abdul-Rahman, Munther A. Gdeisat, David R. Burton, Michael J. Lalor, Francis Lilley, and Christopher J. Moore
Appl. Opt. 46(26) 6623-6635 (2007)

Hybrid robust and fast algorithm for three-dimensional phase unwrapping

Miguel Arevalillo-Herráez, Munther A. Gdeisat, and David R. Burton
Appl. Opt. 48(32) 6313-6323 (2009)

Network approaches to two-dimensional phase unwrapping: intractability and two new algorithms

Curtis W. Chen and Howard A. Zebker
J. Opt. Soc. Am. A 17(3) 401-414 (2000)