Phase Unwrapping Based on Multiple Population Genetic and Simulated Annealing Algorithm

Phase unwrapping is a common problem for many phase measurement techniques which restores original continuous phase from the wrapped phases. There are many phase unwrapping algorithms such as the Branch-Cut method, Quality-Guided method and so on. The Branch-Cut method is one of the most classical algorithms, but it often causes a large number of ‘isolated island’, which affects the quality of unwrapping. This paper develops the traditional Branch-Cut algorithm based on the fact that the branch-cuts problem is equivalent to the travelling salesman problem. The proposed algorithm uses the multiple population genetic and simulated annealing algorithm to calculate optimized match of residues, which effectively reduces the total length of the branch-cuts and avoids the large ‘isolated island’ phenomenon. Experiment results show that the precision and operation time of the proposed algorithm are improved compared with Goldstein’s algorithm.